[Spatio-temporal variation of drought condition during 1961 to 2012 based on composite index of meteorological drought in Altay region, China].

PubMed

Wu, Yan-feng; Bake, Batur; Li, Wei; Wei, Xiao-qin; Wozatihan, Jiayinaguli; Rasulov, Hamid

2015-02-01

Based on the daily meteorological data of seven stations in Altay region, China, this study investigated the temporal ( seasonal, inter-annual and decadal) and spatial variations of drought by using composite index of meteorological drought, as well as trend analysis, M-K abrupt analysis, wavelet analysis and interpolation tools in ArcGIS. The results indicated that the composite index of meteorological drought could reflect the drought condition in Altay region well. Although the frequency and the covered area of both inter-annual and seasonal droughts presented decreasing trends in the recent 52 a, the drought was still serious when considering the annual drought. The frequencies of inter-annual and spring droughts had no abrupt changes, whereas the frequencies of inter-summer, autumn and winter droughts had abrupt changes during the past 52 a. A significant periodic trend was also observed for the frequencies of inter-annual and seasonal droughts. The distribution of frequency and covered area suggested that the conditions of drought were heavily serious in Qinghe County, moderately serious in Altay City, Fuyun County, Buerjin County and Fuhai County, and slightly serious in Habahe County and Jimunai County.

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

NASA Astrophysics Data System (ADS)

Aadhar, Saran; Mishra, Vimal

2017-10-01

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

A Remotely Sensed Global Terrestrial Drought Severity Index

NASA Astrophysics Data System (ADS)

Mu, Q.; Zhao, M.; Kimball, J. S.; McDowell, N. G.; Running, S. W.

2012-12-01

Regional drought and flooding from extreme climatic events are increasing in frequency and severity, with significant adverse eco-social impacts. Detecting and monitoring drought at regional to global scales remains challenging, despite the availability of various drought indices and widespread availability of potentially synergistic global satellite observational records. We developed a method to generate a near-real-time remotely sensed Drought Severity Index (DSI) to monitor and detect drought globally at 1-km spatial resolution and regular 8-day, monthly and annual frequencies. The new DSI integrates and exploits information from current operational satellite based terrestrial evapotranspiration (ET) and Vegetation greenness Index (NDVI) products, which are sensitive to vegetation water stress. Specifically, our approach determines the annual DSI departure from its normal (2000-2011) using the remotely sensed ratio of ET to potential ET (PET) and NDVI. The DSI results were derived globally and captured documented major regional droughts over the last decade, including severe events in Europe (2003), the Amazon (2005 and 2010), and Russia (2010). The DSI corresponded favorably (r=0.43) with the precipitation based Palmer Drought Severity Index (PDSI), while both indices captured similar wetting and drying patterns. The DSI was also correlated with satellite based vegetation net primary production (NPP) records, indicating that the combined use of these products may be useful for assessing water supply and ecosystem interactions, including drought impacts on crop yields and forest productivity. The remotely-sensed global terrestrial DSI enhances capabilities for near-real-time drought monitoring to assist decision makers in regional drought assessment and mitigation efforts, and without many of the constraints of more traditional drought monitoring methods.

Searching for the optimal drought index and timescale combination to detect drought: a case study from the lower Jinsha River basin, China

NASA Astrophysics Data System (ADS)

Fluixá-Sanmartín, Javier; Pan, Deng; Fischer, Luzia; Orlowsky, Boris; García-Hernández, Javier; Jordan, Frédéric; Haemmig, Christoph; Zhang, Fangwei; Xu, Jijun

2018-02-01

Drought indices based on precipitation are commonly used to identify and characterize droughts. Due to the general complexity of droughts, the comparison of index-identified events with droughts at different levels of the complete system, including soil humidity or river discharges, relies typically on model simulations of the latter, entailing potentially significant uncertainties. The present study explores the potential of using precipitation-based indices to reproduce observed droughts in the lower part of the Jinsha River basin (JRB), proposing an innovative approach for a catchment-wide drought detection and characterization. Two indicators, namely the Overall Drought Extension (ODE) and the Overall Drought Indicator (ODI), have been defined. These indicators aim at identifying and characterizing drought events on the basin scale, using results from four meteorological drought indices (standardized precipitation index, SPI; rainfall anomaly index, RAI; percent of normal precipitation, PN; deciles, DEC) calculated at different locations of the basin and for different timescales. Collected historical information on drought events is used to contrast results obtained with the indicators. This method has been successfully applied to the lower Jinsha River basin in China, a region prone to frequent and severe droughts. Historical drought events that occurred from 1960 to 2014 have been compiled and cataloged from different sources, in a challenging process. The analysis of the indicators shows a good agreement with the recorded historical drought events on the basin scale. It has been found that the timescale that best reproduces observed events across all the indices is the 6-month timescale.

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.

Development of a Coastal Drought Index Using Salinity Data

NASA Astrophysics Data System (ADS)

Conrads, P. A.; Darby, L. S.

2014-12-01

The freshwater-saltwater interface in surface-water bodies along the coast is an important factor in the ecological and socio-economic dynamics of coastal communities. It influences community composition in freshwater and saltwater ecosystems, determines fisheries spawning habitat, and controls freshwater availability for municipal and industrial water intakes. These dynamics may be affected by coastal drought through changes in Vibrio bacteria impacts on shellfish harvesting and occurrence of wound infection, fish kills, harmful algal blooms, hypoxia, and beach closures. There are many definitions of drought, with most describing a decline in precipitation having negative impacts on water supply and agriculture. Four general types of drought are recognized: hydrological, agricultural, meteorological, and socio-economic. Indices have been developed for these drought types incorporating data such as rainfall, streamflow, soil moisture, groundwater levels, and snow pack. These indices were developed for upland areas and may not be appropriate for characterizing drought in coastal areas. Because of the uniqueness of drought impacts on coastal ecosystems, a need exists to develop a coastal drought index. The availability of real-time and historical salinity datasets provides an opportunity to develop a salinity-based coastal drought index. The challenge of characterizing salinity dynamics in response to drought is excluding responses attributable to occasional saltwater intrusion events. Our approach to develop a coastal drought index modified the Standardized Precipitation Index and applied it to sites in South Carolina and Georgia, USA. Coastal drought indices characterizing 1-, 3-, 6-, 9-, and12-month drought conditions were developed. Evaluation of the coastal drought index indicates that it can be used for different estuary types, for comparison between estuaries, and as an index for wet conditions (high freshwater inflow) in addition to drought conditions.

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

Comprehensive assessment of drought from 1960 to 2013 in China based on different perspectives

NASA Astrophysics Data System (ADS)

Lai, Wenli; Wang, Hongrui; Zhang, Jie

2017-10-01

Using daily and monthly precipitation data collected from 520 meteorological stations from 1960 to 2013, we compared a widely used drought index, the standardized precipitation index (SPI), with an extreme index, the maximum consecutive dry days index (CDD). Two other homogeneity test methods, namely the Gini coefficient (including both Total-Gini and Wet-Gini) and the precipitation concentration degree (PCD) were also applied to indirectly estimate extreme droughts. The changes in droughts determined using the SPI and the CDD exhibited similar spatial and temporal patterns throughout most parts of China, with the exception of Southwestern China. Comparison of the five indices indicated that Wet-Gini exhibited different or even opposite trends of drought across all of China. Finally, a trend analysis from 2000 to 2013 was applied to perform a regional empirical analysis of a classic extreme drought event in Southwestern China. All indices, except for Wet-Gini, indicated increasing drought risk.

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.

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

NASA Astrophysics Data System (ADS)

Aadhar, S.; Mishra, V.

2017-12-01

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

Dendrochronological assessment of drought severity indices for Panola Mountain Research Watershed, Georgia, U.S.A.

NASA Astrophysics Data System (ADS)

McKee, A.; Aulenbach, B. T.

2015-12-01

Quantifying the relation between drought severity and tree growth is important to predict future growth rates as climate change effects the frequency and severity of future droughts. Two commonly used metrics of drought severity are the Standardized Precipitation Index (SPI) and the Palmer Drought Severity Index (PDSI). These indices are often calculated from proximal weather station data and therefore may not be very accurate at the local watershed scale. The accuracy of these commonly used measures of drought severity was compared to a recently developed, locally calibrated model of water limitation based on the difference between potential and actual evapotranspiration (ETDIFF). Relative accuracies of the drought indices were assessed on the strength of correlations with a 20-year tree-ring index chronology (1986-2006) developed from 22 loblolly pine (Pinus taeda) trees in water-limited landscape positions at the Panola Mountain Research Watershed (PMRW), a 41-hectare forested watershed located in north-central Georgia. We used SPI and PDSI index values from the weather station located at the Atlanta Airport, approximately 36 kilometers from PMRW. ETDIFF was calculated based on precipitation, temperature, runoff, and solar radiation data collected at PMRW. Annual index values for all three drought indices were calculated as the mean value over the growing season (May to September). All three indices had significant Pearson correlations with the tree-ring index (p = 0.044, 0.007, 0.002 for SPI, PDSI, and ETDIFF, respectively). The ETDIFF method had the strongest correlation (R2 = 0.40) compared to SPI and PDSI results (R2 = 0.19 and 0.32, respectively). Results suggest SPI and PDSI provided a general measure of drought conditions, however, the locally calibrated model of water limitation appears to measure drought severity more accurately. Future studies on the ecological effects of drought may benefit from adopting ETDIFF as a measure of drought severity.

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 resource management in California. Furthermore, the presentation provides an overview of the information farmers need for better decision making and how GIDMaPS can be used to improve decision making and reducing drought impacts. Further Reading Hao Z., AghaKouchak A., Nakhjiri N., Farahmand A., 2014, Global Integrated Drought Monitoring and Prediction System, Scientific Data, 1:140001, 1-10, doi: 10.1038/sdata.2014.1. Momtaz F., Nakhjiri N., AghaKouchak A., 2014, Toward a Drought Cyberinfrastructure System, Eos, Transactions American Geophysical Union, 95(22), 182-183, doi:10.1002/2014EO220002. AghaKouchak A., 2014, A Baseline Probabilistic Drought Forecasting Framework Using Standardized Soil Moisture Index: Application to the 2012 United States Drought, Hydrology and Earth System Sciences, 18, 2485-2492, doi: 10.5194/hess-18-2485-2014.

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2009-12-01

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

Automatic design of basin-specific drought indexes for highly regulated water systems

NASA Astrophysics Data System (ADS)

Zaniolo, Marta; Giuliani, Matteo; Castelletti, Andrea Francesco; Pulido-Velazquez, Manuel

2018-04-01

Socio-economic costs of drought are progressively increasing worldwide due to undergoing alterations of hydro-meteorological regimes induced by climate change. Although drought management is largely studied in the literature, traditional drought indexes often fail at detecting critical events in highly regulated systems, where natural water availability is conditioned by the operation of water infrastructures such as dams, diversions, and pumping wells. Here, ad hoc index formulations are usually adopted based on empirical combinations of several, supposed-to-be significant, hydro-meteorological variables. These customized formulations, however, while effective in the design basin, can hardly be generalized and transferred to different contexts. In this study, we contribute FRIDA (FRamework for Index-based Drought Analysis), a novel framework for the automatic design of basin-customized drought indexes. In contrast to ad hoc empirical approaches, FRIDA is fully automated, generalizable, and portable across different basins. FRIDA builds an index representing a surrogate of the drought conditions of the basin, computed by combining all the relevant available information about the water circulating in the system identified by means of a feature extraction algorithm. We used the Wrapper for Quasi-Equally Informative Subset Selection (W-QEISS), which features a multi-objective evolutionary algorithm to find Pareto-efficient subsets of variables by maximizing the wrapper accuracy, minimizing the number of selected variables, and optimizing relevance and redundancy of the subset. The preferred variable subset is selected among the efficient solutions and used to formulate the final index according to alternative model structures. We apply FRIDA to the case study of the Jucar river basin (Spain), a drought-prone and highly regulated Mediterranean water resource system, where an advanced drought management plan relying on the formulation of an ad hoc state index is used for triggering drought management measures. The state index was constructed empirically with a trial-and-error process begun in the 1980s and finalized in 2007, guided by the experts from the Confederación Hidrográfica del Júcar (CHJ). Our results show that the automated variable selection outcomes align with CHJ's 25-year-long empirical refinement. In addition, the resultant FRIDA index outperforms the official State Index in terms of accuracy in reproducing the target variable and cardinality of the selected inputs set.

Multivariate Drought Characterization in India for Monitoring and Prediction

NASA Astrophysics Data System (ADS)

Sreekumaran Unnithan, P.; Mondal, A.

2016-12-01

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

[Applicability of established drought index in Huang-Huai-Hai region based on actual evapotranspiration.

PubMed

Wang, Ying; Wu, Rong Jun; Guo, Zhao Bing

2016-05-01

Based on the modeled products of actual evapotranspiration with NOAH land surface model, the temporal and spatial variations of actual evapotranspiration were analyzed for the Huang-Huai-Hai region in 2002-2010. In the meantime, the agricultural drought index, namely, drought severity index (DSI) was constructed, incorporated with products of MOD17 potential evapotranspiration and MOD13 NDVI. Furthermore, the applicability of established DSI in this region in the whole year of 2002 was investigated based on the Palmer drought severity index (PDSI), the yield reduction rate of winter wheat, and drought severity data. The results showed that the annual average actual evapotranspiration within the survey region increased from the northwest to the southeast, with the maximum of 800-900 mm in the southeast and the minimum less than 300 mm in the northwest. The DSI and PDSI had positive correlation (R 2 =0.61) and high concordance in change trend. They all got the low point (-0.61 and -1.33) in 2002 and reached the peak (0.81 and 0.92) in 2003. The correlation between DSI and yield reduction rate of winter wheat (R 2 =0.43) was more significant than that between PDSI and yield reduction rate of winter wheat (R 2 =0.06). So, the DSI reflected a high spatial resolution of drought pattern and could reflect the region agricultural drought severity and intensity more accurately.

Modification of the Fosberg fire weather index to include drought

Treesearch

Scott L. Goodrick

2002-01-01

The Fosberg fire weather index is a simple tool for evaluating the potential influence of weather on a wildland fire based on temperature, relative humidity and wind speed. A modification to this index that includes the impact of precipitation is proposed. The Keetch-Byram drought index is used to formulate a 'fuel availability' factor that modifies the...

Exploring standardized precipitation evapotranspiration index for drought assessment in Bangladesh.

PubMed

Miah, Md Giashuddin; Abdullah, Hasan Muhammad; Jeong, Changyoon

2017-10-09

Drought is a critical issue, and it has a pressing, negative impact on agriculture, ecosystems, livelihoods, food security, and sustainability. The problem has been studied globally, but its regional or even local dimension is sometimes overlooked. Local-level drought assessment is necessary for developing adaptation and mitigation strategies for that particular region. Keeping this in understanding, an attempt was made to create a detailed assessment of drought characteristics at the local scale in Bangladesh. Standardized precipitation evapotranspiration (SPEI) is a new drought index that mainly considers the rainfall and evapotranspiration data set. Globally, SPEI has become a useful drought index, but its local scale application is not common. SPEI base (0.5° grid data) for 110 years (1901-2011) was utilized to overcome the lack of long-term climate data in Bangladesh. Available weather data (1955-2011) from Bangladesh Meteorology Department (BMD) were analyzed to calculate SPEI weather station using the SPEI calculator. The drivers for climate change-induced droughts were characterized by residual temperature and residual rainfall data from different BMD stations. Grid data (SPEI base ) of 26 stations of BMD were used for drought mapping. The findings revealed that the frequency and intensity of drought are higher in the northwestern part of the country which makes it vulnerable to both extreme and severe droughts. Based on the results, the SPEI-based drought intensity and frequency analyses were carried out, emphasizing Rangpur (northwest region) as a hot spot, to get an insight of drought assessment in Bangladesh. The findings of this study revealed that SPEI could be a valuable tool to understand the evolution and evaluation of the drought induced by climate change in the country. The study also justified the immediate need for drought risk reduction strategies that should lead to relevant policy formulations and agricultural innovations for developing drought adaptation, mitigation, and resilience mechanisms in Bangladesh.

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

PubMed

Farahmand, Alireza; AghaKouchak, Amir; Teixeira, Joao

2015-02-25

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

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

PubMed Central

Farahmand, Alireza; AghaKouchak, Amir; Teixeira, Joao

2015-01-01

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

Drought evaluation using the GRACE terrestrial water storage deficit over the Yangtze River Basin, China.

PubMed

Sun, Zhangli; Zhu, Xiufang; Pan, Yaozhong; Zhang, Jinshui; Liu, Xianfeng

2018-09-01

Droughts are some of the worst natural disasters that bring significant water shortages, economic losses, and adverse social consequences. Gravity Recovery and Climate Experiment (GRACE) satellite data are widely used to characterize and evaluate droughts. In this work, we evaluate drought situations in the Yangtze River Basin (YRB) using the GRACE Texas Center for Space Research (CSR) mascon (mass concentration) data from 2003 to 2015. Drought events are identified by water storage deficits (WSDs) derived from GRACE data, while the drought severity evaluation is based on the water storage deficit index (WSDI), standardized WSD time series, and total water storage deficit (TWSD). The WSDI is subsequently compared with the Palmer drought severity index (PDSI), standardized precipitation index (SPI), standardized precipitation evapotranspiration index (SPEI), and standardized runoff index (SRI). The results indicate the YRB experienced increased wetness during the study period, with WSD values increasing at a rate of 5.20mm/year. Eight drought events are identified, and three major droughts occurred in 2004, 2006, and 2011, with WSDIs of -2.05, -2.38, and -1.30 and TWSDs of -620.96mm, -616.81mm, and -192.44mm, respectively. Our findings suggest that GRACE CSR mascon data can be used effectively to assess drought features in the YRB and that the WSDI facilitates robust and reliable characterization of droughts over large-scale areas. Copyright © 2018 Elsevier B.V. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Drought monitoring with soil moisture active passive (SMAP) measurements

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

Sensitivity of Drought Processes to Runoff Parameterizations in East Asia with the Community Land Model

NASA Astrophysics Data System (ADS)

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

2016-12-01

Drought is one of the most powerful and extensive disasters and has the highest annual average damage among all the disasters. Focusing on East Asia, where over one fifth of all the people in the world live, drought has impacted as well as been projected to impact the region significantly. .Therefore it is critical to reasonably simulate the drought phenomenon in the region and thus this study would focus on the reproducibility of drought with the NCAR CLM. In this study, we examine the propagation of drought processes with different runoff parameterization of CLM in East Asia. Two different schemes are used; TOPMODEL-based and VIC-based schemes, which differentiate the result of runoff through the surface and subsurface runoff parameterization. CLM with different runoff scheme are driven with two atmospheric forcings from CRU/NCEP and NCEP reanalysis data. Specifically, propagation of drought from meteorological, agricultural to hydrologic drought is investigated with different drought indices, estimated with not only model simulated results but also observational data. The indices include the standardized precipitation evapotranspiration index (SPEI), standardized runoff index (SRI) and standardized soil moisture index (SSMI). Based on these indices, the drought characteristics such as intensity, frequency and spatial extent are investigated. At last, such drought assessments would reveal the possible model deficiencies in East Asia. AcknowledgementsThis work was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (2015R1C1A2A01054800) and the Korea Meteorological Administration R&D Program under Grant KMIPA 2015-6180.

Regional Drought Monitoring Based on Multi-Sensor Remote Sensing

NASA Astrophysics Data System (ADS)

Rhee, Jinyoung; Im, Jungho; Park, Seonyoung

2014-05-01

Drought originates from the deficit of precipitation and impacts environment including agriculture and hydrological resources as it persists. The assessment and monitoring of drought has traditionally been performed using a variety of drought indices based on meteorological data, and recently the use of remote sensing data is gaining much attention due to its vast spatial coverage and cost-effectiveness. Drought information has been successfully derived from remotely sensed data related to some biophysical and meteorological variables and drought monitoring is advancing with the development of remote sensing-based indices such as the Vegetation Condition Index (VCI), Vegetation Health Index (VHI), and Normalized Difference Water Index (NDWI) to name a few. The Scaled Drought Condition Index (SDCI) has also been proposed to be used for humid regions proving the performance of multi-sensor data for agricultural drought monitoring. In this study, remote sensing-based hydro-meteorological variables related to drought including precipitation, temperature, evapotranspiration, and soil moisture were examined and the SDCI was improved by providing multiple blends of the multi-sensor indices for different types of drought. Multiple indices were examined together since the coupling and feedback between variables are intertwined and it is not appropriate to investigate only limited variables to monitor each type of drought. The purpose of this study is to verify the significance of each variable to monitor each type of drought and to examine the combination of multi-sensor indices for more accurate and timely drought monitoring. The weights for the blends of multiple indicators were obtained from the importance of variables calculated by non-linear optimization using a Machine Learning technique called Random Forest. The case study was performed in the Republic of Korea, which has four distinct seasons over the course of the year and contains complex topography with a variety of land cover types. Remote sensing data from the Tropical Rainfall Measuring Mission satellite (TRMM) and Moderate Resolution Imaging Spectroradiometer (MODIS), and Advanced Microwave Scanning Radiometer-EOS (AMSR-E) sensors were obtained for the period from 2000 to 2012, and observation data from 99 weather stations, 441 streamflow gauges, as well as the gridded observation data from Asian Precipitation Highly-Resolved Observational Data Integration Towards Evaluation of the Water Resources (APHRODITE) were obtained for validation. The objective blends of multiple indicators helped better assessment of various types of drought, and can be useful for drought early warning system. Since the improved SDCI is based on remotely sensed data, it can be easily applied to regions with limited or no observation data for drought assessment and monitoring.

[Spatio-temporal characteristics of agricultural drought in Shaanxi Province, China based on integrated disaster risk index].

PubMed

He, Bin; Wang, Quan Jiu; Wu, Di; Zhou, Bei Bei

2016-10-01

With the change of climate, agricultural drought has directly threatened the food security. Based on the natural disaster risk theory, we analyzed the spatial and temporal characteristics of agricultural drought in Shanxi Province from 2009 to 2013. Four risk factors (hazard, exposure, vulnerability, and drought resistance ability) were selected with the consideration of influence factors of drought disasters. Subsequently, the index weight was determined by the analytic hierarchy process (AHP) and the aggregative indicator of natural disaster risk was established. The results showed that during the study period, the agricultural drought risk slightly declined in the northern Shaanxi, but increased sharply in the southern Shaanxi, especially in Shangluo City. While for the central part of Shaanxi Province, it maintained good stability, which was the highest in Xianyang City and the lowest in Xi'an City. Generally, the agricultural drought risk in Shaanxi Province gradually increased from south to north.

A data fusion-based drought index

NASA Astrophysics Data System (ADS)

Azmi, Mohammad; Rüdiger, Christoph; Walker, Jeffrey P.

2016-03-01

Drought and water stress monitoring plays an important role in the management of water resources, especially during periods of extreme climate conditions. Here, a data fusion-based drought index (DFDI) has been developed and analyzed for three different locations of varying land use and climate regimes in Australia. The proposed index comprehensively considers all types of drought through a selection of indices and proxies associated with each drought type. In deriving the proposed index, weekly data from three different data sources (OzFlux Network, Asia-Pacific Water Monitor, and MODIS-Terra satellite) were employed to first derive commonly used individual standardized drought indices (SDIs), which were then grouped using an advanced clustering method. Next, three different multivariate methods (principal component analysis, factor analysis, and independent component analysis) were utilized to aggregate the SDIs located within each group. For the two clusters in which the grouped SDIs best reflected the water availability and vegetation conditions, the variables were aggregated based on an averaging between the standardized first principal components of the different multivariate methods. Then, considering those two aggregated indices as well as the classifications of months (dry/wet months and active/non-active months), the proposed DFDI was developed. Finally, the symbolic regression method was used to derive mathematical equations for the proposed DFDI. The results presented here show that the proposed index has revealed new aspects in water stress monitoring which previous indices were not able to, by simultaneously considering both hydrometeorological and ecological concepts to define the real water stress of the study areas.

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

NASA Astrophysics Data System (ADS)

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

2006-12-01

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

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

NASA Astrophysics Data System (ADS)

Li, Xinlu; Lu, Hui; Lyu, Haobo

2017-04-01

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

Construction of prediction intervals for Palmer Drought Severity Index using bootstrap

NASA Astrophysics Data System (ADS)

Beyaztas, Ufuk; Bickici Arikan, Bugrayhan; Beyaztas, Beste Hamiye; Kahya, Ercan

2018-04-01

In this study, we propose an approach based on the residual-based bootstrap method to obtain valid prediction intervals using monthly, short-term (three-months) and mid-term (six-months) drought observations. The effects of North Atlantic and Arctic Oscillation indexes on the constructed prediction intervals are also examined. Performance of the proposed approach is evaluated for the Palmer Drought Severity Index (PDSI) obtained from Konya closed basin located in Central Anatolia, Turkey. The finite sample properties of the proposed method are further illustrated by an extensive simulation study. Our results revealed that the proposed approach is capable of producing valid prediction intervals for future PDSI values.

Sensitivity analysis of the Commonly Used Drought Indices on the different land use Types - Case Study over Turkey

NASA Astrophysics Data System (ADS)

Ersoy, E. N.; Hüsami Afşar, M.; Bulut, B.; Onen, A.; Yilmaz, M. T.

2017-12-01

Droughts are climatic phenomenon that may impact large and small regions alike for long or short time periods and influence society in terms of industrial, agricultural, domestic and many more aspects. The characteristics of the droughts are commonly investigated using indices like Standardized Precipitation Index (SPI), Palmer Drought Severity Index (PDSI), Standardized Precipitation Evapotranspiration Index (SPEI) and Normalized Difference Vegetation Index (NDVI). On the other hand, these indices may not necessarily yield similar performance over different vegetation types. The aim is to analyze the sensitivity of drought indices (SPI, SPEI, PDSI) to vegetation types over different climatic regions in Turkey. Here the magnitude of the drought severity is measured using MODIS NDVI data, while the vegetation type (e.g., non-irrigated arable lands, vineyards, fruit trees and berry plantations, olive groves, pastures, land principally occupied by agriculture) information is obtained using CORINE land cover classification. This study has compared the drought characteristics and vegetation conditions on different land use types using remotely sensed datasets (e.g., CORINE land use data, MODIS NDVI), and commonly used drought indices between 2000 and 2016 using gauge based precipitation and temperature measurements.

Cloud Computing-based Platform for Drought Decision-Making using Remote Sensing and Modeling Products: Preliminary Results for Brazil

NASA Astrophysics Data System (ADS)

Vivoni, E.; Mascaro, G.; Shupe, J. W.; Hiatt, C.; Potter, C. S.; Miller, R. L.; Stanley, J.; Abraham, T.; Castilla-Rubio, J.

2012-12-01

Droughts and their hydrological consequences are a major threat to food security throughout the world. In arid and semiarid regions dependent on irrigated agriculture, prolonged droughts lead to significant and recurring economic and social losses. In this contribution, we present preliminary results on integrating a set of multi-resolution drought indices into a cloud computing-based visualization platform. We focused our initial efforts on Brazil due to a severe, on-going drought in a large agricultural area in the northeastern part of the country. The online platform includes drought products developed from: (1) a MODIS-based water stress index (WSI) based on inferences from normalized difference vegetation index and land surface temperature fields, (2) a volumetric water content (VWC) index obtained from application of the NASA CASA model, and (3) a set of AVHRR-based vegetation health indices obtained from NOAA/NESDIS. The drought indices are also presented in terms of anomalies with respect to a baseline period. Since our main objective is to engage stakeholders and decision-makers in Brazil, we incorporated other relevant geospatial data into the platform, including irrigation areas, dams and reservoirs, administrative units and annual climate information. We will also present a set of use cases developed to help stakeholders explore, query and provide feedback that allowed fine-tuning of the drought product delivery, presentation and analysis tools. Finally, we discuss potential next steps in development of the online platform, including applications at finer resolutions in specific basins and at a coarser global scale.

Improved predictability of droughts over southern Africa using the standardized precipitation evapotranspiration index and ENSO

NASA Astrophysics Data System (ADS)

Manatsa, Desmond; Mushore, Terrence; Lenouo, Andre

2017-01-01

The provision of timely and reliable climate information on which to base management decisions remains a critical component in drought planning for southern Africa. In this observational study, we have not only proposed a forecasting scheme which caters for timeliness and reliability but improved relevance of the climate information by using a novel drought index called the standardised precipitation evapotranspiration index (SPEI), instead of the traditional precipitation only based index, the standardised precipitation index (SPI). The SPEI which includes temperature and other climatic factors in its construction has a more robust connection to ENSO than the SPI. Consequently, the developed ENSO-SPEI prediction scheme can provide quantitative information about the spatial extent and severity of predicted drought conditions in a way that reflects more closely the level of risk in the global warming context of the sub region. However, it is established that the ENSO significant regional impact is restricted only to the period December-March, implying a revisit to the traditional ENSO-based forecast scheme which essentially divides the rainfall season into the two periods, October to December and January to March. Although the prediction of ENSO events has increased with the refinement of numerical models, this work has demonstrated that the prediction of drought impacts related to ENSO is also a reality based only on observations. A large temporal lag is observed between the development of ENSO phenomena (typically in May of the previous year) and the identification of regional SPEI defined drought conditions. It has been shown that using the Southern Africa Regional Climate Outlook Forum's (SARCOF) traditional 3-month averaged Nino 3.4 SST index (June to August) as a predictor does not have an added advantage over using only the May SST index values. In this regard, the extended lead time and improved skill demonstrated in this study could immensely benefit regional decision makers.

Global drought outlook by means of seasonal forecasts

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Comparison of satellite-derived LAI and precipitation anomalies over Brazil with a thermal infrared-based Evaporative Stress Index for 2003-2013

USDA-ARS?s Scientific Manuscript database

Shortwave vegetation index (VI) and leaf area index (LAI) remote sensing products yield inconsistent depictions of biophysical response to drought and pluvial events that have occurred in Brazil over the past decade. Conflicting reports of severity of drought impacts on vegetation health and funct...

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

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

Application of Dynamic naïve Bayesian classifier to comprehensive drought assessment

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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.

The use of infrared thermal imaging as a non-destructive screening tool for identifying drought-tolerant lentil genotypes.

PubMed

Biju, Sajitha; Fuentes, Sigfredo; Gupta, Dorin

2018-06-01

Lentil (Lens culinaris, Medik.) is an important legume crop, which often experience drought stress especially at the flowering and grain filling phenological stages. The availability of efficient and robust screening tools based on relevant non-destructive quantifiable traits would facilitate research on crop improvement for drought tolerance. The objective of this study was to evaluate the drought tolerance of 37 lentil genotypes using infrared thermal imaging (IRTI), drought tolerance parameters and multivariate data analysis. Potted plants were kept in a completely randomized design in a growth chamber with five replicates. Plants were subjected to three different drought treatments: 100, 50 and 20% of field capacity at the onset of reproductive period. The relative drought stress tolerance was determined based on a set of morpho-physiological parameters including non-destructive measures based on IRTI, such as: canopy temperature (Tc), canopy temperature depression (CTD) and crop water stress index (CWSI) during the growing period and destructive measures at harvest, such as: dry root-shoot ratio (RS ratio), relative water content (RWC) and harvest index (HI). The drought tolerance indices used were drought susceptibility index (DSI) and drought tolerance efficiency (DTE). Results showed that drought stress treatments significantly reduced the RWC, HI, CTD and DSI, whereas, the values of Tc, CWSI, RS ratio and DTE significantly increased for all the genotypes. The cluster analysis from morpho-physiological parameters clustered genotypes in three distinctive groups as per the level of drought stress tolerance. The genotypes with higher values of RS ratio, RWC, HI, DTE and CTD and lower values of DSI, Tc and CWSI were identified as drought-tolerant genotypes. Based on this preliminary screening, the genotypes Digger, Cumra, Indianhead, ILL 5588, ILL 6002 and ILL 5582 were identified as promising drought-tolerant genotypes. It can be concluded that the IRTI analysis is a high-throughput constructive screening tool along with RS ratio, RWC, HI and other drought tolerance indices to define the drought stress tolerance variability within lentil plants. These results provide a foundation for future research directed at identifying powerful drought assessment traits using rapid and non-destructive techniques, such as IRTI along with the yield traits, and understanding the biochemical and molecular mechanisms underlying lentil tolerance to drought stress. Copyright © 2018 Elsevier Masson SAS. All rights reserved.

Extreme Historical Droughts in the South-Eastern Alps — Analyses Based on Standardised Precipitation Index

NASA Astrophysics Data System (ADS)

Brenčič, Mihael

2016-10-01

Droughts are natural phenomena affecting the environment and human activities. There are various drought definitions and quantitative indices; among them is the Standardised Precipitation Index (SPI). In the drought investigations, historical events are poorly characterised and little data are available. To decipher past drought appearances in the southeastern Alps with a focus on Slovenia, precipitation data from HISTALP data repository were taken to identify extreme drought events (SPI ≤ -2.00) from the second half of the 19th century to the present day. Several long-term extreme drought crises were identified in the region (between the years 1888 and 1896; after World War I, during and after World War II). After 1968, drought patterns detected with SPI changed: shorter, extreme droughts with different time patterns appeared. SPI indices of different time spans showed correlated structures in space and between each other, indicating structured relations.

Research on Applicability Analysis of Drought Index in Liaoning Area

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

Entropy-Aided Evaluation of Meteorological Droughts Over China

NASA Astrophysics Data System (ADS)

Sang, Yan-Fang; Singh, Vijay P.; Hu, Zengyun; Xie, Ping; Li, Xinxin

2018-01-01

Evaluation of drought and its spatial distribution is essential to develop mitigation measures. In this study, we employed the entropy index to investigate the spatiotemporal variability of meteorological droughts over China. Entropy values, with a reliable hydrological and geographical basis, are closely related to the months of precipitation deficit and its mean magnitude and can thus represent the physical formation of droughts. The value of entropy index can be roughly classified as <0.35, 0.36-0.90, and >0.90, reflecting high, middle, and low occurrence probabilities of droughts. The accumulated precipitation deficits, based on the standardized precipitation-evapotranspiration index at the 1, 3, 6, and 12 month scales, consistently increase with entropy decrease, no matter considering the moderately, severely, or extremely dry conditions. Therefore, Northwest China and North China, with smaller entropy values, have higher occurrence probability of droughts than South China, with a break at 38°N latitude. The aggravating droughts in North China and Southwest China over recent decades are represented by the increase in both the occurrence frequency and the magnitude. The entropy, determined by absolute magnitude of the difference between precipitation and potential evapotranspiration, as well as its scatter and skewness characteristics, is easily calculated and can be an effective index for evaluating drought and its spatial distribution. We therefore identified dominant thresholds for entropy values and statistical characteristics of precipitation deficit, which would help evaluate the occurrence probability of droughts worldwide.

Drought Analysis of the Haihe River Basin Based on GRACE Terrestrial Water Storage

PubMed Central

Wang, Jianhua; Jiang, Dong; Huang, Yaohuan; Wang, Hao

2014-01-01

The Haihe river basin (HRB) in the North China has been experiencing prolonged, severe droughts in recent years that are accompanied by precipitation deficits and vegetation wilting. This paper analyzed the water deficits related to spatiotemporal variability of three variables of the gravity recovery and climate experiment (GRACE) derived terrestrial water storage (TWS) data, precipitation, and EVI in the HRB from January 2003 to January 2013. The corresponding drought indices of TWS anomaly index (TWSI), precipitation anomaly index (PAI), and vegetation anomaly index (AVI) were also compared for drought analysis. Our observations showed that the GRACE-TWS was more suitable for detecting prolonged and severe droughts in the HRB because it can represent loss of deep soil water and ground water. The multiyear droughts, of which the HRB has sustained for more than 5 years, began in mid-2007. Extreme drought events were detected in four periods at the end of 2007, the end of 2009, the end of 2010, and in the middle of 2012. Spatial analysis of drought risk from the end of 2011 to the beginning of 2012 showed that human activities played an important role in the extent of drought hazards in the HRB. PMID:25202732

Drought analysis of the Haihe river basin based on GRACE terrestrial water storage.

PubMed

Wang, Jianhua; Jiang, Dong; Huang, Yaohuan; Wang, Hao

2014-01-01

The Haihe river basin (HRB) in the North China has been experiencing prolonged, severe droughts in recent years that are accompanied by precipitation deficits and vegetation wilting. This paper analyzed the water deficits related to spatiotemporal variability of three variables of the gravity recovery and climate experiment (GRACE) derived terrestrial water storage (TWS) data, precipitation, and EVI in the HRB from January 2003 to January 2013. The corresponding drought indices of TWS anomaly index (TWSI), precipitation anomaly index (PAI), and vegetation anomaly index (AVI) were also compared for drought analysis. Our observations showed that the GRACE-TWS was more suitable for detecting prolonged and severe droughts in the HRB because it can represent loss of deep soil water and ground water. The multiyear droughts, of which the HRB has sustained for more than 5 years, began in mid-2007. Extreme drought events were detected in four periods at the end of 2007, the end of 2009, the end of 2010, and in the middle of 2012. Spatial analysis of drought risk from the end of 2011 to the beginning of 2012 showed that human activities played an important role in the extent of drought hazards in the HRB.

Drought evolution, severity and trends in mainland China over 1961-2013.

PubMed

Yao, Ning; Li, Yi; Lei, Tianjie; Peng, Lingling

2018-03-01

Droughts have destructive impacts on crop yields and water supplies, and researching droughts is vital for societal stability and human life. This work aimed to assess the spatiotemporal evolution of droughts in mainland China over 1961-2013 using four drought indices. These indices were the percentage of precipitation anomaly (Pa), standard precipitation index (SPI), standard precipitation evapotranspiration index (SPEI) and evaporative demand drought index (EDDI) at multiple timescales ranging from 1-week to 24-month. The variations of the SPI, SPEI and EDDI were compared with historical severe or extreme droughts. The general increases of the Pa, SPI and SPEI, and general decrease of the EDDI, consistently implied an overall relief of drought conditions over 1961-2013. The different drought indices revealed historical drought conditions, including the national extreme droughts in 1961, 1965, 1972, 1978, 1986, 1988, 1992, 1994, 1997, 1999 and 2000, but various drought severity levels were classified for each drought event since the classification standards differed. Although the SPI and SPEI performed better than the EDDI and there were higher correlations between the SPI and the SPEI, all the indices were regional- or station-specific and have identified historical severe or extreme drought events. At shorter timescales, the EDDI revealed earlier onsets and ends of flash droughts, unlike those indicated by the SPI and SPEI. The comparison of the different indices based on the historical drought events confirmed the uses of the Pa, SPI and SPEI for determining continuous droughts and that of the EDDI for identifying flash droughts. Copyright © 2017 Elsevier B.V. All rights reserved.

Development of a coastal drought index using salinity data

USGS Publications Warehouse

Conrads, Paul; Darby, Lisa S.

2017-01-01

A critical aspect of the uniqueness of coastal drought is the effects on the salinity dynamics of creeks, rivers, and estuaries. The location of the freshwater–saltwater interface along the coast is an important factor in the ecological and socioeconomic dynamics of coastal communities. Salinity is a critical response variable that integrates hydrologic and coastal dynamics including sea level, tides, winds, precipitation, streamflow, and tropical storms. The position of the interface determines the composition of freshwater and saltwater aquatic communities as well as the freshwater availability for water intakes. Many definitions of drought have been proposed, with most describing a decline in precipitation having negative impacts on the water supply. Indices have been developed incorporating data such as rainfall, streamflow, soil moisture, and groundwater levels. These water-availability drought indices were developed for upland areas and may not be ideal for characterizing coastal drought. The availability of real-time and historical salinity datasets provides an opportunity for the development of a salinity-based coastal drought index. An approach similar to the standardized precipitation index (SPI) was modified and applied to salinity data obtained from sites in South Carolina and Georgia. Using the SPI approach, the index becomes a coastal salinity index (CSI) that characterizes coastal salinity conditions with respect to drought periods of higher-saline conditions and wet periods of higher-freshwater conditions. Evaluation of the CSI indicates that it provides additional coastal response information as compared to the SPI and the Palmer hydrologic drought index, and the CSI can be used for different estuary types and for comparison of conditions along coastlines.

A hybrid framework for assessing maize drought vulnerability in Sub-Saharan Africa

NASA Astrophysics Data System (ADS)

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

2017-12-01

Drought has devastating impacts on crop yields. Quantifying drought vulnerability is the first step to better design of mitigation policies. The vulnerability of crop yield to drought has been assessed with different methods, however they lack a standardized base to measure its components and a procedure that facilitates spatial and temporal comparisons. This study attempts to quantify maize drought vulnerability through linking the Drought Exposure Index (DEI) to the Crop Failure Index (CFI). DEI and CFI were defined by fitting probability distribution functions to precipitation and maize yield respectively. To acquire crop drought vulnerability index (CDVI), DEI and CFI were combined in a hybrid framework which classifies CDVI with the same base as DEI and CFI. The analysis were implemented on Sub-Saharan African countries using maize yield simulated with the Environmental Policy Integrated Climate (EPIC) model at 0.5° resolution. The model was coupled with the Sequential Uncertainty Fitting algorithm for calibration at country level. Our results show that Central Africa and those Western African countries located below the Sahelian strip receive higher amount of precipitation, but experience high crop failure. Therefore, they are identified as more vulnerable regions compared to countries such as South Africa, Tanzania, and Kenya. We concluded that our hybrid approach complements information on crop drought vulnerability quantification and can be applied to different regions and scales.

Understanding Atmospheric Anomalies Associated with Seasonal Pluvial-Drought Processes Using Southwest China as an Example

NASA Astrophysics Data System (ADS)

Liu, Z.; LU, G.; He, H.; Wu, Z.; He, J.

2017-12-01

Seasonal pluvial-drought transition processes are unique natural phenomena. To explore possible mechanisms, we considered Southwest China (SWC) as the study region and comprehensively investigated the temporal evolution of large-scale and regional atmospheric variables with the simple method of Standardized Anomalies (SA). Some key results include: (1) The net vertical integral of water vapour flux (VIWVF) across the four boundaries may be a feasible indicator of pluvial-drought transition processes over SWC, because its SA-based index is almost consistent with process development. (2) The vertical SA-based patterns of regional horizontal divergence (D) and vertical motion (ω) also coincides with the pluvial-drought transition processes well, and the SA-based index of regional D show relatively high correlation with the identified processes over SWC. (3) With respect to large-scale anomalies of circulation patterns, a well-organized Eurasian Pattern is one important feature during the pluvial-drought transition over SWC. (4) To explore the possibility of simulating drought development using previous pluvial anomalies, large-scale and regional atmospheric SA-based indices were used. As a whole, when SA-based indices of regional dynamic and water-vapor variables are introduced, simulated drought development only with large-scale anomalies can be improved a lot. (5) Eventually, pluvial-drought transition processes and associated regional atmospheric anomalies over nine Chinese drought study regions were investigated. With respect to regional D, vertically single or double "upper-positive-lower-negative" and "upper-negative-lower-positive" patterns are the most common vertical SA-based patterns during the pluvial and drought parts of transition processes, respectively.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

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.

Drought Risk Assessment based on Natural and Social Factors

NASA Astrophysics Data System (ADS)

Huang, Jing; Wang, Huimin; Han, Dawei

2015-04-01

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

Towards Developing a Regional Drought Information System for Lower Mekong

NASA Astrophysics Data System (ADS)

Dutta, R.; Jayasinghe, S.; Basnayake, S. B.; Apirumanekul, C.; Pudashine, J.; Granger, S. L.; Andreadis, K.; Das, N. N.

2016-12-01

With the climate and weather patterns changing over the years, the Lower Mekong Basin have been experiencing frequent and prolonged droughts resulting in severe damage to the agricultural sector affecting food security and livelihoods of the farming community. However, the Regional Drought Information System (RDIS) for Lower Mekong countries would help prepare vulnerable communities from frequent and severe droughts through monitoring, assessing and forecasting of drought conditions and allowing decision makers to take effective decisions in terms of providing early warning, incentives to farmers, and adjustments to cropping calendars and so on. The RDIS is an integrated system that is being designed for drought monitoring, analysis and forecasting based on the need to meet the growing demand of an effective monitoring system for drought by the lower Mekong countries. The RDIS is being built on four major components that includes earth observation component, meteorological data component, database storage and Regional Hydrologic Extreme Assessment System (RHEAS) framework while the outputs from the system will be made open access to the public through a web-based user interface. The system will run on the RHEAS framework that allows both nowcasting and forecasting using hydrological and crop simulation models such as the Variable Infiltration Capacity (VIC) model and the Decision Support System for Agro-Technology Transfer (DSSAT) model respectively. The RHEAS allows for a tightly constrained observation based drought and crop yield information system that can provide customized outputs on drought that includes root zone soil moisture, Standard Precipitation Index (SPI), Standard Runoff Index (SRI), Palmer Drought Severity Index (PDSI) and Crop Yield and can integrate remote sensing products, along with evapotranspiration and soil moisture data. The anticipated outcomes from the RDIS is to improve the operational, technological and institutional capabilities of lower Mekong countries to prepare for and respond towards drought situations and providing policy makers with current and forecast drought indices for decision making on adjusting cropping calendars as well as planning short and long term mitigation measures.

Remotely Sensed Quantitative Drought Risk Assessment in Vulnerable Agroecosystems

NASA Astrophysics Data System (ADS)

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

2012-04-01

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

Bias correction of precipitation data and its effects on aridity and drought assessment in China over 1961-2015.

PubMed

Yao, Ning; Li, Yi; Li, Na; Yang, Daqing; Ayantobo, Olusola Olaitan

2018-10-15

The accuracy of gauge-measured precipitation (P m ) affects drought assessment since drought severity changes due to precipitation bias correction. This research investigates how drought severity changes as the result of bias-corrected precipitation (P c ) using the Erinc's index I m and standardized precipitation evapotranspiration index (SPEI). Daily and monthly P c values at 552 sites in China were determined using daily P m and wind speed and air temperature data over 1961-2015. P c -based I m values were generally larger than P m -based I m for most sub-regions in China. The increased P c and P c -based I m values indicated wetter climate conditions than previously reported for China. After precipitation bias-correction, Climate types changed, e.g., 20 sites from severe-arid to arid, and 11 sites from arid to semi-arid. However, the changes in SPEI were not that obvious due to precipitation bias correction because the standardized index SPEI removed the effects of mean precipitation values. In conclusion, precipitation bias in different sub-regions of China changed the spatial and temporal characteristics of drought assessment. Copyright © 2018 Elsevier B.V. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

A new comprehensive index for drought monitoring with TM data

NASA Astrophysics Data System (ADS)

Wang, Yuanyuan

2017-10-01

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

Evaluation of ET-based drought index derived from geostationary satellite data

USDA-ARS?s Scientific Manuscript database

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

Evaluation of Drought Implications on Ecosystem Services: Freshwater Provisioning and Food Provisioning in the Upper Mississippi River Basin

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

Li, Ping; Omani, Nina; Chaubey, Indrajeet

Drought is one of the most widespread extreme climate events with a potential to alter freshwater availability and related ecosystem services. Given the interconnectedness between freshwater availability and many ecosystem services, including food provisioning, it is important to evaluate the drought implications on freshwater provisioning and food provisioning services. Studies about drought implications on streamflow, nutrient loads, and crop yields have been increased and these variables are all process-based model outputs that could represent ecosystem functions that contribute to the ecosystem services. However, few studies evaluate drought effects on ecosystem services such as freshwater and food provisioning and quantify thesemore » services using an index-based ecosystem service approach. In this study, the drought implications on freshwater and food provisioning services were evaluated for 14 four-digit HUC (Hydrological Unit Codes) subbasins in the Upper Mississippi River Basin (UMRB), using three drought indices: standardized precipitation index (SPI), standardized soil water content index (SSWI), and standardized streamflow index (SSI). The results showed that the seasonal freshwater provisioning was highly affected by the precipitation deficits and/or surpluses in summer and autumn. A greater importance of hydrological drought than meteorological drought implications on freshwater provisioning was evident for the majority of the subbasins, as evidenced by higher correlations between freshwater provisioning and SSI12 than SPI12. Food provisioning was substantially affected by the precipitation and soil water deficits during summer and early autumn, with relatively less effect observed in winter. A greater importance of agricultural drought effects on food provisioning was evident for most of the subbasins during crop reproductive stages. Results from this study may provide insights to help make effective land management decisions in responding to extreme climate conditions in order to protect and restore freshwater provisioning and food provisioning services in the UMRB.« less

Evaluation of Drought Implications on Ecosystem Services: Freshwater Provisioning and Food Provisioning in the Upper Mississippi River Basin.

PubMed

Li, Ping; Omani, Nina; Chaubey, Indrajeet; Wei, Xiaomei

2017-05-08

Drought is one of the most widespread extreme climate events with a potential to alter freshwater availability and related ecosystem services. Given the interconnectedness between freshwater availability and many ecosystem services, including food provisioning, it is important to evaluate the drought implications on freshwater provisioning and food provisioning services. Studies about drought implications on streamflow, nutrient loads, and crop yields have been increased and these variables are all process-based model outputs that could represent ecosystem functions that contribute to the ecosystem services. However, few studies evaluate drought effects on ecosystem services such as freshwater and food provisioning and quantify these services using an index-based ecosystem service approach. In this study, the drought implications on freshwater and food provisioning services were evaluated for 14 four-digit HUC (Hydrological Unit Codes) subbasins in the Upper Mississippi River Basin (UMRB), using three drought indices: standardized precipitation index ( SPI ), standardized soil water content index ( SSWI ), and standardized streamflow index ( SSI ). The results showed that the seasonal freshwater provisioning was highly affected by the precipitation deficits and/or surpluses in summer and autumn. A greater importance of hydrological drought than meteorological drought implications on freshwater provisioning was evident for the majority of the subbasins, as evidenced by higher correlations between freshwater provisioning and SSI 12 than SPI 12. Food provisioning was substantially affected by the precipitation and soil water deficits during summer and early autumn, with relatively less effect observed in winter. A greater importance of agricultural drought effects on food provisioning was evident for most of the subbasins during crop reproductive stages. Results from this study may provide insights to help make effective land management decisions in responding to extreme climate conditions in order to protect and restore freshwater provisioning and food provisioning services in the UMRB.

Evaluation of Drought Implications on Ecosystem Services: Freshwater Provisioning and Food Provisioning in the Upper Mississippi River Basin

PubMed Central

Li, Ping; Omani, Nina; Chaubey, Indrajeet; Wei, Xiaomei

2017-01-01

Drought is one of the most widespread extreme climate events with a potential to alter freshwater availability and related ecosystem services. Given the interconnectedness between freshwater availability and many ecosystem services, including food provisioning, it is important to evaluate the drought implications on freshwater provisioning and food provisioning services. Studies about drought implications on streamflow, nutrient loads, and crop yields have been increased and these variables are all process-based model outputs that could represent ecosystem functions that contribute to the ecosystem services. However, few studies evaluate drought effects on ecosystem services such as freshwater and food provisioning and quantify these services using an index-based ecosystem service approach. In this study, the drought implications on freshwater and food provisioning services were evaluated for 14 four-digit HUC (Hydrological Unit Codes) subbasins in the Upper Mississippi River Basin (UMRB), using three drought indices: standardized precipitation index (SPI), standardized soil water content index (SSWI), and standardized streamflow index (SSI). The results showed that the seasonal freshwater provisioning was highly affected by the precipitation deficits and/or surpluses in summer and autumn. A greater importance of hydrological drought than meteorological drought implications on freshwater provisioning was evident for the majority of the subbasins, as evidenced by higher correlations between freshwater provisioning and SSI12 than SPI12. Food provisioning was substantially affected by the precipitation and soil water deficits during summer and early autumn, with relatively less effect observed in winter. A greater importance of agricultural drought effects on food provisioning was evident for most of the subbasins during crop reproductive stages. Results from this study may provide insights to help make effective land management decisions in responding to extreme climate conditions in order to protect and restore freshwater provisioning and food provisioning services in the UMRB. PMID:28481311

Evaluation of Drought Implications on Ecosystem Services: Freshwater Provisioning and Food Provisioning in the Upper Mississippi River Basin

DOE PAGES

Li, Ping; Omani, Nina; Chaubey, Indrajeet; ...

2017-05-08

Drought is one of the most widespread extreme climate events with a potential to alter freshwater availability and related ecosystem services. Given the interconnectedness between freshwater availability and many ecosystem services, including food provisioning, it is important to evaluate the drought implications on freshwater provisioning and food provisioning services. Studies about drought implications on streamflow, nutrient loads, and crop yields have been increased and these variables are all process-based model outputs that could represent ecosystem functions that contribute to the ecosystem services. However, few studies evaluate drought effects on ecosystem services such as freshwater and food provisioning and quantify thesemore » services using an index-based ecosystem service approach. In this study, the drought implications on freshwater and food provisioning services were evaluated for 14 four-digit HUC (Hydrological Unit Codes) subbasins in the Upper Mississippi River Basin (UMRB), using three drought indices: standardized precipitation index (SPI), standardized soil water content index (SSWI), and standardized streamflow index (SSI). The results showed that the seasonal freshwater provisioning was highly affected by the precipitation deficits and/or surpluses in summer and autumn. A greater importance of hydrological drought than meteorological drought implications on freshwater provisioning was evident for the majority of the subbasins, as evidenced by higher correlations between freshwater provisioning and SSI12 than SPI12. Food provisioning was substantially affected by the precipitation and soil water deficits during summer and early autumn, with relatively less effect observed in winter. A greater importance of agricultural drought effects on food provisioning was evident for most of the subbasins during crop reproductive stages. Results from this study may provide insights to help make effective land management decisions in responding to extreme climate conditions in order to protect and restore freshwater provisioning and food provisioning services in the UMRB.« less

Assessment of Drought Scenario in Western Nepal

NASA Astrophysics Data System (ADS)

Pandey, V. P.; Khatiwada, K. R.

2017-12-01

Drought is a frequent phenomenon in relatively drier western Nepal. Lack of hydro-climatic information with wider spatial coverage is hindering effective assessment of the drought events. Furthermore, drought assessment is not getting adequate attention in Nepal. This study aims to develop drought scenario for Western Nepal by evaluating various types of drought indices in Karnali River Basin (area = 4,6150 km2) and recommend the most suited set of indices for data-poor regions. On the climatic data at ten stations, drought indices were calculated from following seven selected indices: Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI), Palmer Drought Severity Index (PDSI), (self-calibrating) Palmer Drought Severity Index (scPDSI), Reconnaissance Drought Index (RDI), Standardized Streamflow Index (SSFI), and Palmer Hydrological Drought Index (PHDI). Initial results reflect that the basin is affected by severe meteorological drought. Most of the indices show the extreme dryness scenario during the years 1984-85, 1992-93, 1995, 2000, 20002, 2008-09, and 2012. The results from the stations with long-term temperature and precipitation data sets showed a higher (up to 0.9) correlation between SPI and RDI than for SPEI and other Palmer Drought Indices, which ranged from 0.6 to 0.8 only. This suggests ability of SPI to represent magnitude and duration of the drought events fairly well in the study basin, and therefore, has potential to represent drought dynamics in data-poor regions. Keywords: Drought; Karnali River Basin; Nepal Himalaya

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

USDA-ARS?s Scientific Manuscript database

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

Potential evapotranspiration and the likelihood of future drought

NASA Technical Reports Server (NTRS)

Rind, D.; Hansen, J.; Goldberg, R.; Rosenzweig, C.; Ruedy, R.

1990-01-01

The possibility that the greenhouse warming predicted by the GISS general-circulation model and other GCMs could lead to severe droughts is investigated by means of numerical simulations, with a focus on the role of potential evapotranspiration E(P). The relationships between precipitation (P), E(P), soil moisture, and vegetation changes in GCMs are discussed; the empirically derived Palmer drought-intensity index and a new supply-demand index (SDDI) based on changes in P - E(P) are described; and simulation results for the period 1960-2060 are presented in extensive tables, graphs, and computer-generated color maps. Simulations with both drought indices predict increasing drought frequency for the U.S., with effects already apparent in the 1990s and a 50-percent frequency of severe droughts by the 2050s. Analyses of arid periods during the Mesozoic and Cenozoic are shown to support the use of the SDDI in GCM drought prediction.

A Generalized Framework for Different Drought Indices: Testing its Suitability in a Simulation of the last two Millennia for Europe

NASA Astrophysics Data System (ADS)

Raible, Christoph C.; Baerenbold, Oliver; Gomez-Navarro, Juan Jose

2016-04-01

Over the past decades, different drought indices have been suggested in the literature. This study tackles the problem of how to characterize drought by defining a general framework and proposing a generalized family of drought indices that is flexible regarding the use of different water balance models. The sensitivity of various indices and its skill to represent drought conditions is evaluated using a regional model simulation in Europe spanning the last two millennia as test bed. The framework combines an exponentially damped memory with a normalization method based on quantile mapping. Both approaches are more robust and physically meaningful compared to the existing methods used to define drought indices. Still, framework is flexible with respect to the water balance, enabling users to adapt the index formulation to the data availability of different locations. Based on the framework, indices with different complex water balances are compared with each other. The comparison shows that a drought index considering only precipitation in the water balance is sufficient for Western to Central Europe. However, in the Mediterranean temperature effects via evapotranspiration need to be considered in order to produce meaningful indices representative of actual water deficit. Similarly, our results indicate that in north-eastern Europe and Scandinavia, snow and runoff effects needs to be considered in the index definition to obtain accurate results.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Development of a SMAP-Based Drought Monitoring Product

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Widespread extreme drought events in Iberia and their relationship with North Atlantic moisture flux deficit

NASA Astrophysics Data System (ADS)

Liberato, Margarida L. R.; Montero, Irene; Russo, Ana; Gouveia, Célia; Ramos, Alexandre M.; Trigo, Ricardo M.

2015-04-01

Droughts represent one of the most frequent climatic extreme events on the Iberian Peninsula, often with widespread negative ecological and environmental impacts, resulting in major socio-economic damages such as large decreases in hydroelectricity and agricultural productions or increasing forest fire risk. Unlike other weather driven extreme events, droughts duration could be from few months to several years. Here we employ a recently developed climatic drought index, the Standardized Precipitation Evapotranspiration Index (SPEI; Vicente-Serrano et al. 2010a), based on the simultaneous use of precipitation and temperature fields. This index holds the advantage of combining a multi-scalar character with the capacity to include the effects of temperature variability on drought assessment (Vicente-Serrano et al., 2010a). In this study the SPEI was computed using the Climatic Research Unit (CRU) TS3.21 High Resolution Gridded Data (0.5°) for the period 1901-2012. At this resolution the study region of Iberian Peninsula corresponds to a square of 30x30 grid pixels. The CRU Potential Evapotranspiration (PET) was used, through the Penmann-Monteith equation and the log-logistic probability distribution. This formulation allows a very good fit to the series of differences between precipitation and PET (Vicente-Serrano et al., 2010b), using monthly averages of daily maximum and minimum temperature data and also monthly precipitation records. The parameters were estimated by means of the L-moment method. The application of multi-scalar indices to the high-resolution datasets allows identifying whether the Iberian Peninsula is in hydric stress and also whether drought is installed. Based on the gridded SPEI datasets, spanning from 1901 to 2012, obtained for timescales 6, 12, 18 and 24 months, an objective method is applied for ranking the most extensive extreme drought events that occurred on the Iberian Peninsula. This objective method is based on the evaluation of the drought's magnitude, which is obtained after considering the area affected - defined by SPEI values over a certain threshold (in this case SPEI < -1.28) - as well as its intensity in each grid point. Different rankings are presented for the different timescales considering both the entire Iberian Peninsula and Portugal. Furthermore we used the NCEP/NCAR reanalysis in the 1948-2012 period, namely, the geopotential height, temperature, wind and specific humidity fields at all pressure levels and mean sea level pressure (MSLP) and total column water vapour (TCWV) for the Euro-Atlantic sector (60° W to 40° E, 20° N to 70° N) at full temporal (six hourly) and spatial (2.5° regular horizontal grid) resolutions available as well as the globally gridded monthly precipitation products of the Global Precipitation Climatology Centre (GPCC), to analyse the large-scale conditions associated with the most extreme droughts in Iberia. Results show that during these drought periods there is a clear moisture deficit over the region, with permanent negative anomalies of TCWV. Additionally, in these occasions, the zonal moisture transport is more intense over the northern Atlantic and less intense on the subtropics while the meridional moisture transport is intensified, in accordance with the barotropic structure of HGT anomalies. Vicente-Serrano, S.M., Beguería, S., and López-Moreno, J.I. (2010a). A Multi-scalar drought index sensitive to global warming: The Standardized Precipitation Evapotranspiration Index - SPEI. Journal of Climate, 23, 1696-1718. Vicente-Serrano, S.M., Beguería, S., López-Moreno, J.I., Angulo, M., and El Kenawy, A. (2010b). A new global 0.5° gridded dataset (1901-2006) of a multiscalar drought index: comparison with current drought index datasets based on the Palmer Drought Severity Index. Journal of Hydrometeorology, 11, 1033-1043 Acknowledgements: This work was partially supported by national funds through FCT (Fundação para a Ciência e a Tecnologia, Portugal) under project QSECA (PTDC/AAGGLO/4155/2012).

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

Forecasting SPEI and SPI Drought Indices Using the Integrated Artificial Neural Networks

PubMed Central

Maca, Petr; Pech, Pavel

2016-01-01

The presented paper compares forecast of drought indices based on two different models of artificial neural networks. The first model is based on feedforward multilayer perceptron, sANN, and the second one is the integrated neural network model, hANN. The analyzed drought indices are the standardized precipitation index (SPI) and the standardized precipitation evaporation index (SPEI) and were derived for the period of 1948–2002 on two US catchments. The meteorological and hydrological data were obtained from MOPEX experiment. The training of both neural network models was made by the adaptive version of differential evolution, JADE. The comparison of models was based on six model performance measures. The results of drought indices forecast, explained by the values of four model performance indices, show that the integrated neural network model was superior to the feedforward multilayer perceptron with one hidden layer of neurons. PMID:26880875

Forecasting SPEI and SPI Drought Indices Using the Integrated Artificial Neural Networks.

PubMed

Maca, Petr; Pech, Pavel

2016-01-01

The presented paper compares forecast of drought indices based on two different models of artificial neural networks. The first model is based on feedforward multilayer perceptron, sANN, and the second one is the integrated neural network model, hANN. The analyzed drought indices are the standardized precipitation index (SPI) and the standardized precipitation evaporation index (SPEI) and were derived for the period of 1948-2002 on two US catchments. The meteorological and hydrological data were obtained from MOPEX experiment. The training of both neural network models was made by the adaptive version of differential evolution, JADE. The comparison of models was based on six model performance measures. The results of drought indices forecast, explained by the values of four model performance indices, show that the integrated neural network model was superior to the feedforward multilayer perceptron with one hidden layer of neurons.

Multi-index evaluation of future drought and climate extreme occurrence in Goodwater Creek Experimental Watershed

USDA-ARS?s Scientific Manuscript database

Understanding the frequency and occurrence of drought events in historic and projected future climate is essential for managing natural resources and setting policy. This study aims to identify future patterns of meteorological, hydrological and agricultural droughts based on projection from 12 GCM ...

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 loss was highest in Sichuan Province and Chongqing Municipality. It was lowest in Yunnan province. The comprehensive drought disaster loss were uptrend in nearly 60 years, and the trend of drought occurrence in nearly 60 years was overall upward in every province of Xinan region. Drought risk of all provinces has certain relationship with the regional climate change, such as temperature and precipitation, soil moisture and vegetation coverage. The contribution of the risk factors to R was highest for the capacity for prevention and mitigation, followed by the drought hazard, sensitivity and exposure, and environmental vulnerability.

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

NASA Astrophysics Data System (ADS)

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

2012-11-01

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

Hydrologic Drought in the Colorado River Basin

NASA Astrophysics Data System (ADS)

Timilsena, J.; Piechota, T.; Hidalgo, H.; Tootle, G.

2004-12-01

This paper focuses on drought scenarios of the Upper Colorado River Basin (UCRB) for the last five hundred years and evaluates the magnitude, severity and frequency of the current five-year drought. Hydrologic drought characteristics have been developed using the historical streamflow data and tree ring chronologies in the UCRB. Historical data include the Colorado River at Cisco and Lees Ferry, Green River, Palmer Hydrologic Drought Index (PHDI), and the Z index. Three ring chronologies were used from 17 spatially representative sites in the UCRB from NOAA's International Tree Ring Data. A PCA based regression model procedures was used to reconstruct drought indices and streamflow in the UCRB. Hydrologic drought is characterized by its duration (duration in year in which cumulative deficit is continuously below thresholds), deficit magnitude (the cumulative deficit below the thresholds for consecutive years), severity (magnitude divided by the duration) and frequency. Results indicate that the current drought ranks anywhere from the 5th to 20th worst drought during the period 1493-2004, depending on the drought indicator and magnitude. From a short term perspective (using annual data), the current drought is more severe than if longer term average (i.e., 5 or 10 year averages) are used to define the drought.

Identification and simulation of space-time variability of past hydrological drought events in the Limpopo River basin, southern Africa

NASA Astrophysics Data System (ADS)

Trambauer, P.; Maskey, S.; Werner, M.; Pappenberger, F.; van Beek, L. P. H.; Uhlenbrook, S.

2014-08-01

Droughts are widespread natural hazards and in many regions their frequency seems to be increasing. A finer-resolution version (0.05° × 0.05°) of the continental-scale hydrological model PCRaster Global Water Balance (PCR-GLOBWB) was set up for the Limpopo River basin, one of the most water-stressed basins on the African continent. An irrigation module was included to account for large irrigated areas of the basin. The finer resolution model was used to analyse hydrological droughts in the Limpopo River basin in the period 1979-2010 with a view to identifying severe droughts that have occurred in the basin. Evaporation, soil moisture, groundwater storage and runoff estimates from the model were derived at a spatial resolution of 0.05° (approximately 5 km) on a daily timescale for the entire basin. PCR-GLOBWB was forced with daily precipitation and temperature obtained from the ERA-Interim global atmospheric reanalysis product from the European Centre for Medium-Range Weather Forecasts. Two agricultural drought indicators were computed: the Evapotranspiration Deficit Index (ETDI) and the Root Stress Anomaly Index (RSAI). Hydrological drought was characterised using the Standardized Runoff Index (SRI) and the Groundwater Resource Index (GRI), which make use of the streamflow and groundwater storage resulting from the model. Other more widely used meteorological drought indicators, such as the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evaporation Index (SPEI), were also computed for different aggregation periods. Results show that a carefully set-up, process-based model that makes use of the best available input data can identify hydrological droughts even if the model is largely uncalibrated. The indicators considered are able to represent the most severe droughts in the basin and to some extent identify the spatial variability of droughts. Moreover, results show the importance of computing indicators that can be related to hydrological droughts, and how these add value to the identification of hydrological droughts and floods and the temporal evolution of events that would otherwise not have been apparent when considering only meteorological indicators. In some cases, meteorological indicators alone fail to capture the severity of the hydrological drought. Therefore, a combination of some of these indicators (e.g. SPEI-3, SRI-6 and SPI-12 computed together) is found to be a useful measure for identifying agricultural to long-term hydrological droughts in the Limpopo River basin. Additionally, it was possible to undertake a characterisation of the drought severity in the basin, indicated by its time of occurrence, duration and intensity.

Identification and simulation of space-time variability of past hydrological drought events in the Limpopo river basin, Southern Africa

NASA Astrophysics Data System (ADS)

Trambauer, P.; Maskey, S.; Werner, M.; Pappenberger, F.; van Beek, L. P. H.; Uhlenbrook, S.

2014-03-01

Droughts are widespread natural hazards and in many regions their frequency seems to be increasing. A finer resolution version (0.05° x 0.05°) of the continental scale hydrological model PCR-GLOBWB was set up for the Limpopo river basin, one of the most water stressed basins on the African continent. An irrigation module was included to account for large irrigated areas of the basin. The finer resolution model was used to analyse droughts in the Limpopo river basin in the period 1979-2010 with a view to identifying severe droughts that have occurred in the basin. Evaporation, soil moisture, groundwater storage and runoff estimates from the model were derived at a spatial resolution of 0.05° (approximately 5 km) on a daily time scale for the entire basin. PCR-GLOBWB was forced with daily precipitation, temperature and other meteorological variables obtained from the ERA-Interim global atmospheric reanalysis product from the European Centre for Medium-Range Weather Forecasts. Two agricultural drought indicators were computed: the Evapotranspiration Deficit Index (ETDI) and the Root Stress Anomaly Index (RSAI). Hydrological drought was characterised using the Standardized Runoff Index (SRI) and the Groundwater Resource Index (GRI), which make use of the streamflow and groundwater storage resulting from the model. Other more widely used drought indicators, such as the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evaporation Index (SPEI) were also computed for different aggregation periods. Results show that a carefully set up process-based model that makes use of the best available input data can successfully identify hydrological droughts even if the model is largely uncalibrated. The indicators considered are able to represent the most severe droughts in the basin and to some extent identify the spatial variability of droughts. Moreover, results show the importance of computing indicators that can be related to hydrological droughts, and how these add value to the identification of droughts/floods and the temporal evolution of events that would otherwise not have been apparent when considering only meteorological indicators. In some cases, meteorological indicators alone fail to capture the severity of the drought. Therefore, a combination of some of these indicators (e.g. SPEI-3, SRI-6, SPI-12) is found to be a useful measure for identifying hydrological droughts in the Limpopo river basin. Additionally, it is possible to make a characterisation of the drought severity, indicated by its duration and intensity.

Use of Drought Index and Crop Modelling for Drought Impacts Analysis on Maize (Zea mays L.) Yield Loss in Bandung District

NASA Astrophysics Data System (ADS)

Kurniasih, E.; Impron; Perdinan

2017-03-01

Drought impacts on crop yield loss depend on drought magnitude and duration and on plant genotype at every plant growth stages when droughts occur. This research aims to assess the difference calculation results of 2 drought index methods and to study the maize yield loss variability impacted by drought magnitude and duration during maize growth stages in Bandung district, province of West Java, Indonesia. Droughts were quantified by the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI) at 1- to 3-month lags for the January1986-December 2015 period data. Maize yield responses to droughts were simulated by AquaCrop for the January 1986-May 2016 period of growing season. The analysis showed that the SPI and SPEI methods provided similar results in quantifying drought event. Droughts during maize reproductive stages caused the highest maize yield loss.

Indices and Dynamics of Global Hydroclimate Over the Past Millennium from Data Assimilation

NASA Astrophysics Data System (ADS)

Steiger, N. J.; Smerdon, J. E.

2017-12-01

Reconstructions based on data assimilation (DA) are at the forefront of model-data syntheses in that such reconstructions optimally fuse proxy data with climate models. DA-based paleoclimate reconstructions have the benefit of being physically-consistent across the reconstructed climate variables and are capable of providing dynamical information about past climate phenomena. Here we use a new implementation of DA, that includes updated proxy system models and climate model bias correction procedures, to reconstruct global hydroclimate on seasonal and annual timescales over the last millennium. This new global hydroclimate product includes reconstructions of the Palmer Drought Severity Index, the Standardized Precipitation Evapotranspiration Index, and global surface temperature along with dynamical variables including the Nino 3.4 index, the latitudinal location of the intertropical convergence zone, and an index of the Atlantic Multidecadal Oscillation. Here we present a validation of the reconstruction product and also elucidate the causes of severe drought in North America and in equatorial Africa. Specifically, we explore the connection between droughts in North America and modes of ocean variability in the Pacific and Atlantic oceans. We also link drought over equatorial Africa to shifts of the intertropical convergence zone and modes of ocean variability.

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

PubMed

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

2017-01-01

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

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

PubMed Central

Yuan, Yanbin; You, Lin; Chen, Chao

2017-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Innovation in drought risk management: exploring the potential of weather index insurance

NASA Astrophysics Data System (ADS)

Iglesias, E.; Baez, K.

2012-04-01

Many family farming and indigenous communities depend on grazing livestock activities and are particularly prone to drought risks. Vulnerability to drought limits the ability of these households to exit poverty and in many cases leads to environmental degradation. It is well known that uninsured exposure exacerbates income inequality in farming systems and eventually results in welfare losses for rural families. The advantages of farmers who have access to financial tools have been widely acknowledged. However, high administrative costs of traditional insurance hinder small farmers' access to risk management tools. One of the main problems in insurance design relates to the lack of quality data to estimate the risk premium. In rural areas where there are no historical records of farm production data on adverse events such as drought. New technologies such as remote sensing help to overcome this problem and generate information from these areas that otherwise would be impossible or too expensive to obtain. In this paper, we use a satellite based vegetation index (NDVI) and develop a stochastic model to analyse the potential of index insurance to address the risk of drought in Chilean grazing lands. Our results suggest that contract design is a key issue to improve the correlation of the index with individual farm losses, thus reducing basis risk. In particular, we find that the definition of homogeneous areas and the selection of the triggering index threshold are critical issues and show the incidence of different contract designs on (i) the probability that the farmer experience losses but does not receive compensation (false negative) and (ii) the probability that the index triggers compensation but the farmer does not experience drought losses (false negative). Both aspects are key issues to offer the farmer an adequate protection against droughts and guarantee the affordability of the risk premium.

Global Assessment of Groundwater Sustainability Based On Storage Anomalies

NASA Astrophysics Data System (ADS)

Thomas, Brian F.; Caineta, Júlio; Nanteza, Jamiat

2017-11-01

The world's largest aquifers are a fundamental source of freshwater used for agricultural irrigation and to meet human water needs. Therefore, their stored volume of groundwater is linked with water security, which becomes more relevant during periods of drought. This work focuses on understanding large-scale groundwater changes, where we introduce an approach to evaluate groundwater sustainability at a global scale. We employ a groundwater drought index to assess performance metrics (reliability, resilience, vulnerability, and a combined sustainability index) for the largest and most productive global aquifers. Spatiotemporal changes in total water storage are derived from remote sensing observations of gravity anomalies, from which the groundwater drought index is inferred. The results reveal a complex relationship between the indicators, while considering monthly variability in groundwater storage. Combining the drought and sustainability indexes, as presented in this work, constitutes a measure for quantifying groundwater sustainability. This framework integrates changes in groundwater resources due to human influences and climate changes, thus opening a path to assess progress toward sustainable use and water security.

Future changes to drought characteristics over the Canadian Prairie Provinces based on NARCCAP multi-RCM ensemble

NASA Astrophysics Data System (ADS)

Masud, M. B.; Khaliq, M. N.; Wheater, H. S.

2017-04-01

This study assesses projected changes to drought characteristics in Alberta, Saskatchewan and Manitoba, the prairie provinces of Canada, using a multi-regional climate model (RCM) ensemble available through the North American Regional Climate Change Assessment Program. Simulations considered include those performed with six RCMs driven by National Center for Environmental Prediction reanalysis II for the 1981-2003 period and those driven by four Atmosphere-Ocean General Circulation Models for the 1970-1999 and 2041-2070 periods (i.e. eleven current and the same number of corresponding future period simulations). Drought characteristics are extracted using two drought indices, namely the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI). Regional frequency analysis is used to project changes to selected 20- and 50-year regional return levels of drought characteristics for fifteen homogeneous regions, covering the study area. In addition, multivariate analyses of drought characteristics, derived on the basis of 6-month SPI and SPEI values, are developed using the copula approach for each region. Analysis of multi-RCM ensemble-averaged projected changes to mean and selected return levels of drought characteristics show increases over the southern and south-western parts of the study area. Based on bi- and trivariate joint occurrence probabilities of drought characteristics, the southern regions along with the central regions are found highly drought vulnerable, followed by the southwestern and southeastern regions. Compared to the SPI-based analysis, the results based on SPEI suggest drier conditions over many regions in the future, indicating potential effects of rising temperatures on drought risks. These projections will be useful in the development of appropriate adaptation strategies for the water and agricultural sectors, which play an important role in the economy of the study area.

Integrated meteorological and hydrological drought model: A management tool for proactive water resources planning of semi-arid regions

NASA Astrophysics Data System (ADS)

Rad, Arash Modaresi; Ghahraman, Bijan; Khalili, Davar; Ghahremani, Zahra; Ardakani, Samira Ahmadi

2017-09-01

Conventionally, drought analysis has been limited to single drought category. Utilization of models incorporating multiple drought categories, can relax this limitation. A copula-based model is proposed, which uses meteorological and hydrological drought characteristics to assess drought events for ultimate management of water resources, at small scales, i.e., sub-watersheds. The chosen study area is a sub-basin located at Karkheh watershed (western Iran), with five raingauge stations and one hydrometric station, located upstream and at the outlet, respectively, which represent 41-year of data. Prior to drought analysis, time series of precipitation and streamflow records are investigated for possible dependency/significant trend. Considering semi-arid nature of the study area, boxplots are utilized to graphically capture the rainy months, which are used to evaluate the degree of correlation between streamflow and precipitation records via nonparametric correlations. Time scales of 3- and 12-month are considered, which are used to study vulnerability of early vegetation establishment and long-term ecosystem resilience, respectively. Among four common goodness of fit (GOF) tests, Anderson-Darling is found preferable for defining copula distribution functions through GOF measures, i.e., Akaike and Bayesian information criteria and normalized root mean square error. Furthermore, a GOF method is proposed to evaluate the uncertainty associated with different copula models using the concept of entropy. A new bivariate drought modeling approach is proposed through copulas. The proposed index named standardized precipitation-streamflow index (SPSI) unlike common indices which are used in conjunction with station data, can be applied on a regional basis. SPDI is compared with widely applied streamflow drought index (SDI) and standardized precipitation index (SPI). To assess the homogeneity of the dependence structure of SPSI regionally, Kendall-τ and upper tail coefficient relation is investigated for all stations located within the region. According to results, SPSI similar to nonparametric multivariate standardized drought index (NMSDI) was able to detect both onset of droughts dominated by precipitation as is similarly indicated by SPI and persistence of droughts dominated by streamflow as is similarly indicated by SDI. It also captures discordant case of normal period precipitation with dry period streamflow and vice versa. This makes SPSI a powerful tool for estimating a more practical and realistic drought condition. Finally, combination of severity-duration-frequency (SDF) of drought events through copulas resulted in SDF curves that can be used to obtain the recurrence of extreme droughts and assess drought related ecosystem failure or to aid in optimization of water resources allocation. Results indicated that the newly proposed index (SPSI) is able to represent two main characteristics of meteorological and hydrological drought (drought onset and persistency) and also providing an accurate estimation of the recurrence interval of extreme droughts. The procedures can be used to undertake proactive water resource management and planning to assure water security and sustainable agriculture and ecosystem survival for regions experiencing extreme droughts.

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

NASA Astrophysics Data System (ADS)

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

2013-04-01

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

Drought assessment for cropland of Central America using course-resolution remote sensing data

NASA Astrophysics Data System (ADS)

Chen, C. F.; Nguyen, S. T.; Chen, C. R.; Chiang, S. H.; Chang, L. Y.; Khin, L. V.

2015-12-01

Drought is one of the most frequent and costliest natural disasters, which imposes enormous effects to human societies and ecosystems. Agricultural drought is referred to an interval of time, such as weeks or months, when the soil moisture supply of a region consistently falls below the appropriate moisture supply leading to negative impacts on agricultural production. Millions of households in Central America were dependent upon major food crops, including maize, beans, and sorghum, for their daily subsistence. In recent years, impacts of climate change through global warming in forms of higher temperature and widespread rainfall deficits have however triggered severe drought during the primera cropping season (April-August) in the study region, causing profound impacts on agriculture, crop production losses, increased market food prices, as well as food security issues. This study focuses on investigating agricultural droughts for cropland of Central America using the Moderate Resolution Imaging Spectroradiometer (MODIS) data. We processed the data for a normal year 2013 and an abnormal year 2014 using a simple vegetation health index (VHI) that is developed based on the temperature condition index (TCI) and vegetation condition index (VCI). The VHI results were validated using the Advanced Microwave Scanning Radiometer 2 (AMSR2) precipitation data and temperature vegetation dryness index (TVDI) that is developed based on the empirical analysis of TCI and VCI data. The correlation coefficients (r) obtained by comparisons between the VHI data and the AMSR2 precipitation and TVDI data were higher than 0.62 and -0.61, respectively. The severe drought was intensive during the dry season (January-April) and likely backed to normal conditions in May with the onset of rainy season. The larger area of serve drought was observed for the 2014 primera season, especially during April-July. When investigating the cultivated areas affected by severe drought in the primera season, the total cropland areas affected (by severe drought) observed for 2013 and 2014 were 2,463 km2 and 3,874 km2, respectively. This study demonstrates the applicability of MODIS data for agricultural drought monitoring in Central America.

Spatiotemporal variability and assessment of drought in the Wei River basin of China

NASA Astrophysics Data System (ADS)

Cai, Siyang; Zuo, Depeng; Xu, Zongxue; Han, Xianming; Gao, Xiaoxi

2018-06-01

The temporal and spatial variations of drought in the Wei River basin (WRB) were investigated by calculating the meteorological drought Index (Standardized Precipitation Index, SPI) and the agricultural drought index (Vegetation Health Index, VHI). Monthly precipitation and air temperature were from 22 meteorological stations over the region from 1960 to 2015. Monthly Normalized Difference Vegetation Index (NDVI) and 8-days Land Surface Temperature (LST) were provided from the National Aeronautics and Space Administration (NASA) for the period 2000-2015 were also adopted. The results showed that the drought initially increased and then decreased, reaching at the maximum value in 1990s. The spatial pattern of meteorological drought showed that the drought in northern WRB was heavier than that in southern WRB before 1990s, after that, the situation had the opposite. By comparing the agricultural drought index (VHI) with crop yield, it was proved that VHI was applicable in the WRB and could well reflect the fluctuation of agricultural drought. The WRB suffered from serious agricultural drought in 2000, 2001, 2007 and 2008. Through analysis of the historical precipitation and temperature data, it was found that precipitation had a greater contribution to creating agricultural drought conditions than temperature in the Wei River basin.

Drought Assessment over the Four Major River Basins of India using GRACE-based estimates of Water Availability

NASA Astrophysics Data System (ADS)

Sinha, D.; Syed, T. H.

2017-12-01

Drought is a natural disaster that has mutilating consequences over agriculture, ecosystems, economy and the society. Over the past few decades, drought related catastrophe, associated with global climate change, has escalated all across the world. Identification and analysis of drought utilizing individual hydrologic variables may be inadequate owing to the multitude of factors that are associated with the phenomenon. Therefore it is crucial to develop techniques that warrant comprehensive monitoring and assessment of droughts. In this study we propose a novel drought index (Water Availability Index (WAI)) that comprehends all the aspects of meteorologic, agricultural and hydrologic droughts. The proposed framework underscores the conceptualization and utilization of water availability, quantified as an integrated estimate of land water storage, using Gravity Recovery and Climate Experiment (GRACE) observations, and precipitation. The methodology is employed over four major river basins of India (i.e. Ganga, Krishna, Godavari and Mahanadi) for a period of 155 months (April 2002 to February 2015). Results exhibit the potential of the propounded index (WAI) to recognize drought events and impart insightful quantification of drought severity. WAI also demonstrates enhanced outcomes in comparison to other commonly used drought indices like PDSI, SPI, SPEI and SRI. In general there are at least three major drought periods with intensities ranging from moderate to severe in almost all river basins. The longest drought period, extending for 27 months, from September 2008 to November 2010, is observed in the Mahanadi basin. Results from this study confirm the potential of this technique as an effective tool for the characterization of drought at large spatial scales, which will only excel with better quantification and extended availability of terrestrial water storage observations from the GRACE-Follow On mission.

Performing drought indices to identify the relationship between agricultural losses and drought events in Spain.

NASA Astrophysics Data System (ADS)

Peña Gallardo, Marina; Serrano, Sergio Martín Vicente; Portugués Santiago, Beguería; Burguera Miquel, Tomás

2017-04-01

Drought leads to crop failures reducing the productivity. For this reason, the need of appropriate tool for recognize dry periods and evaluate the impact of drought on crop production is important. In this study, we provide an assessment of the relationship between drought episodes and crop failures in Spain as one of the direct consequences of drought is the diminishing of crop yields. First, different drought indices [the Standardized Precipitation and Evapotranspiration Index (SPEI); the Standardized Precipitation Index (SPI); the self-calibrated Palmer Moisture Anomaly Index (Z-Index), the self-calibrated Crop Moisture Index (CMI) and the Standardized Palmer Drought Index (SPDI)] have been calculated at different time scales in order to identify the dry events occurred in Spain and determine the duration and intensity of each event. Second, the drought episodes have been correlated with crop production estimated and final crop production data provided by the Spanish Crop Insurance System for the available period from 1995 to 2014 at the municipal spatial scale, with the purpose of knowing if the characteristics of the drought episodes are reflected on the agricultural losses. The analysis has been carried out in particular for two types of crop, wheat and barley. The results indicate the existence of an agreement between the most important drought events in Spain and the response of the crop productions and the proportion of hectare insurance. Nevertheless, this agreement vary depending on the drought index applied. Authors found a higher competence of the drought indices calculated at different time scales (SPEI, SPI and SPDI) identifying the begging and end of the drought events and the correspondence with the crop failures.

Development of a global Agricultural Stress Index System (ASIS) based on remote sensing data

NASA Astrophysics Data System (ADS)

Van Hoolst, R.

2016-12-01

According to the 2012 IPCC SREX report, extreme drought events are projected to become more frequent and intense in several regions of the world. Wide and timely monitoring systems are required to mitigate the impact of agricultural drought. Therefore, FAO's Global Information and Early Warning System (GIEWS) and the Climate, Energy and Tenure Division (NRC) have established the `Agricultural Stress Index System' (ASIS). The ASIS is a remote sensing application that provides early warnings of agricultural drought at a global scale. The ASIS has first been designed and described by Rojas et al. (2011). This study focused on the African continent and was based on the back processing of low resolution data of the NOAA-satellites. In the current setup, developed by VITO (Flemish Institute for Technological Research), the system operates in Near Real Time using data from the METOP-AVHRR sensor. The Agricultural Stress Index (ASI) is the percentage of agricultural area affected by drought in the course of the growing season within a given administrative unit. The start and end of the growing season are derived per pixel from the long term NDVI average of SPOT-VEGETATION. The Global Administrative Unit Layer (GAUL) defines the administrative boundaries at level 0, 1 and 2. A global cropland and grassland map eliminates non-agricultural areas. Temperature and NDVI anomalies are used as drought indicators and calculated at a per pixel base. The ASIS aggregates this information and produces every dekad global maps to highlight hotspots of drought stress. New developments are ongoing to strengthen the ASIS to produce country specific outputs, improve existing drought indicators and estimate production deficits using a probabilistic approach.

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

PubMed

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

2017-02-01

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

Historical extension of operational NDVI products for livestock insurance in Kenya

NASA Astrophysics Data System (ADS)

Vrieling, Anton; Meroni, Michele; Shee, Apurba; Mude, Andrew G.; Woodard, Joshua; de Bie, C. A. J. M. (Kees); Rembold, Felix

2014-05-01

Droughts induce livestock losses that severely affect Kenyan pastoralists. Recent index insurance schemes have the potential of being a viable tool for insuring pastoralists against drought-related risk. Such schemes require as input a forage scarcity (or drought) index that can be reliably updated in near real-time, and that strongly relates to livestock mortality. Generally, a long record (>25 years) of the index is needed to correctly estimate mortality risk and calculate the related insurance premium. Data from current operational satellites used for large-scale vegetation monitoring span over a maximum of 15 years, a time period that is considered insufficient for accurate premium computation. This study examines how operational NDVI datasets compare to, and could be combined with the non-operational recently constructed 30-year GIMMS AVHRR record (1981-2011) to provide a near-real time drought index with a long term archive for the arid lands of Kenya. We compared six freely available, near-real time NDVI products: five from MODIS and one from SPOT-VEGETATION. Prior to comparison, all datasets were averaged in time for the two vegetative seasons in Kenya, and aggregated spatially at the administrative division level at which the insurance is offered. The feasibility of extending the resulting aggregated drought indices back in time was assessed using jackknifed R2 statistics (leave-one-year-out) for the overlapping period 2002-2011. We found that division-specific models were more effective than a global model for linking the division-level temporal variability of the index between NDVI products. Based on our results, good scope exists for historically extending the aggregated drought index, thus providing a longer operational record for insurance purposes. We showed that this extension may have large effects on the calculated insurance premium. Finally, we discuss several possible improvements to the drought index.

Ecological and meteorological drought monitoring in East Asia

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Sensitivity of vegetation indices and gross primary production of tallgrass prairie to severe drought

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

Wagle, Pradeep; Xiao, Xiangming; Torn, Margaret S.

2014-09-01

Drought affects vegetation photosynthesis and growth.Many studies have used the normalized difference vegetation index (NDVI), which is calculated as the normalized ratio between near infrared and red spectral bands in satellite images, to evaluate the response of vegetation to drought. In this study, we examined the impacts of drought on three vegetation indices (NDVI, enhanced vegetation index, EVI, and land surface water index, LSWI) and CO2 flux from three tallgrass prairie eddy flux tower sites in the U.S. Gross primary production (GPP) was also modeled using a satellite-based Vegetation Photosynthesis Model (VPM), and the modeled GPP (GPPVPM) was compared withmore » the GPP (GPPEC) derived from eddy covariance measurements. Precipitation at two sites in Oklahoma was 30% below the historical mean in both years of the study period (2005–2006), while the site in Illinois did not experience drought in the 2005–2007 study period. The EVI explained the seasonal dynamics of GPP better than did NDVI. The LSWI dropped below zero during severe droughts in the growing season, showing its potential to track drought. The result shows that GPP was more sensitive to drought than were vegetation indices, and EVI and LSWI were more sensitive than NDVI. We developed a modified function (Wscalar), calculated as a function of LSWI, to account for the effect of severe droughts on GPP in VPM. The GPPVPM from the modified VPM accounted for the rapid reduction in GPP during severe droughts and the seasonal dynamics of GPPVPM agreed reasonably well with GPPEC. Our analysis shows that 8-day averaged values (temperature, vapor-pressure deficit) do not reflect the short-term extreme climate events well, suggesting that satellite based models may need to be run at daily or hourly scales, especially under unfavorable climatic conditions.« less

Influence of mathematical and physical background of drought indices on their complementarity and drought recognition ability

NASA Astrophysics Data System (ADS)

Frank, Anna; Armenski, Tanja; Gocic, Milan; Popov, Srdjan; Popovic, Ljiljana; Trajkovic, Slavisa

2017-09-01

The aim of this study is to test how effective and physically correct are the mathematical approaches of operational indices used by relevant National Agencies across the globe. To do so, the following indices were analysed Standardized Precipitation Index (SPI) -1, 3, 6, 12 and 24, Standardized Precipitation - Evapotranspiration Index (SPEI) - 1, 3, 6, 12 and 24, Effective Drought Index (EDI) and Index of Drying Efficiency of Air (IDEA). To make regions more comparable to each other and follow the spatial development of drought SPI index was advised by World Meteorological Organisation to be used widely by official meteorological services. The SPI and SPEI are used for Drought Early Warning in the USA, National Drought Mitigation Center and NASA, and in the EU by the European Drought Centre (EDC) and in the Balkan Region by National Meteorological Agencies. The EDI Index has wide application in Asia. In this paper four different issues were investigated: 1) how the mathematical method used in a drought indicator's computation influence drought indices' (DI) comparative analyses; 2) the sensitivity of the DIs on any change of the length of observational period; 3) similarities between the DIs time series; 4) and how accurate DIs are when compared to historical drought records. Results suggest that it is necessary to apply a few crucial changes in the Drought Monitoring and Early Warning Systems: 1) reconsider use of SPI and SPEI family indices as a measure of quality of other indices; and for Drought Early Recognition Programs 2) switch to DIs with a solid physical background, such as EDI; 3) Adopt solid physics for modelling drought processes and define the physical measure of drought, e.g. EDI and IDEA indices; 4) investigate further the IDEA index, which, supported by our study as well, is valuable for simulation of a drought process.

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

PubMed

Yi, Hang; Wen, Lianxing

2016-01-27

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

Spatiotemporal Variability of Drought in Pakistan through High-Resolution Daily Gridded In-Situ Observations

NASA Astrophysics Data System (ADS)

Bashir, F.; Zeng, X.; Gupta, H. V.; Hazenberg, P.

2017-12-01

Drought as an extreme event may have far reaching socio-economic impacts on agriculture based economies like Pakistan. Effective assessment of drought requires high resolution spatiotemporally continuous hydrometeorological information. For this purpose, new in-situ daily observations based gridded analyses of precipitation, maximum, minimum and mean temperature and diurnal temperature range are developed, that covers whole Pakistan on 0.01º latitude-longitude for a 54-year period (1960-2013). The number of participating meteorological observatories used in these gridded analyses is 2 to 6 times greater than any other similar product available. This data set is used to identify extreme wet and dry periods and their spatial patterns across Pakistan using Palmer Drought Severity Index (PDSI) and Standardized Precipitation Index (SPI). Periodicity of extreme events is estimated at seasonal to decadal scales. Spatiotemporal signatures of drought incidence indicating its extent and longevity in different areas may help water resource managers and policy makers to mitigate the severity of the drought and its impact on food security through suitable adaptive techniques. Moreover, this high resolution gridded in-situ observations of precipitation and temperature is used to evaluate other coarser-resolution gridded products.

Is drought helping or killing dengue? Investigation of spatiotemporal relationship between dengue fever and drought

NASA Astrophysics Data System (ADS)

Lee, Chieh-Han; Yu, Hwa-Lung

2015-04-01

Dengue Fever is a vector-borne disease that is transmitted between human and mosquitos in tropical and sub-tropical regions. Previous studies have found significant relationship between the epidemic of dengue cases and climate variables, especially temperature and precipitation. Besides, the natural phenomena (e.g., drought) are considered that significantly drop the number of dengue cases by killing vector's breeding environment. However, in Kaohsiung City, Taiwan, there are evidences that the temporal pattern of dengue is correlated to drought events. Kaohsiung City experienced two main dengue outbreaks in 2002 and 2014 that both years were confirmed with serious drought. Especially in 2014, Kaohsiung City was suffered from extremely dengue outbreak in 2014 that reported the highest number of dengue cases in the history. This study constructs the spatiotemporal model of dengue incidences and index of drought events (Standardized Precipitation Index, SPI) based on the distributed lag nonlinear model (DLNM). Other meteorological measures are also included in the analysis.

Characterising droughts in Central America with uncertain hydro-meteorological data

NASA Astrophysics Data System (ADS)

Quesada Montano, B.; Westerberg, I.; Wetterhall, F.; Hidalgo, H. G.; Halldin, S.

2015-12-01

Droughts studies are scarce in Central America, a region frequently affected by droughts that cause significant socio-economic and environmental problems. Drought characterisation is important for water management and planning and can be done with the help of drought indices. Many indices have been developed in the last decades but their ability to suitably characterise droughts depends on the region of application. In Central America, comprehensive and high-quality observational networks of meteorological and hydrological data are not available. This limits the choice of drought indices and denotes the need to evaluate the quality of the data used in their calculation. This paper aimed to find which combination(s) of drought index and meteorological database are most suitable for characterising droughts in Central America. The drought indices evaluated were the standardised precipitation index (SPI), deciles (DI), the standardised precipitation evapotranspiration index (SPEI) and the effective drought index (EDI). These were calculated using precipitation data from the Climate Hazards Group Infra-Red Precipitation with station (CHIRPS), CRN073, the Climate Research Unit (CRU), ERA-Interim and station databases, and temperature data from the CRU database. All the indices were calculated at 1-, 3-, 6-, 9- and 12-month accumulation times. As a first step, the large-scale meteorological precipitation datasets were compared to have an overview of the level of agreement between them and find possible quality problems. Then, the performance of all the combinations of drought indices and meteorological datasets were evaluated against independent river discharge data, in form of the standardised streamflow index (SSI). Results revealed the large disagreement between the precipitation datasets; we found the selection of database to be more important than the selection of drought index. We found that the best combinations of meteorological drought index and database were obtained using the SPI and DI, calculated with CHIRPS and station data.

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.

NDVI statistical distribution of pasture areas at different times in the Community of Madrid (Spain)

NASA Astrophysics Data System (ADS)

Martín-Sotoca, Juan J.; Saa-Requejo, Antonio; Díaz-Ambrona, Carlos G. H.; Tarquis, Ana M.

2015-04-01

The severity of drought has many implications for society, including its impacts on the water supply, water pollution, reservoir management and ecosystem. However, its impacts on rain-fed agriculture are especially direct. Because of the importance of drought, there have been many attempts to characterize its severity, resulting in the numerous drought indices that have been developed (Niemeyer 2008). 'Biomass index' based on satellite image derived Normalized Difference Vegetation Index (NDVI) has been used in countries like United States of America, Canada and Spain for pasture and forage crops for some years (Rao, 2010). This type of agricultural insurance is named as 'index-based insurance' (IBI). IBI is perceived to be substantially less costly to operate and manage than multiple peril insurance. IBI contracts pay indemnities based not on the actual yield (or revenue) losses experienced by the insurance purchaser but rather based on realized NDVI values (historical data) that is correlated with farm-level losses (Xiaohui Deng et al., 2008). Definition of when drought event occurs is defined on NDVI threshold values mainly based in statistical parameters, average and standard deviation that characterize a normal distribution. In this work a pasture area at the north of Community of Madrid (Spain) has been delimited. Then, NDVI historical data was reconstructed based on remote sensing imaging MODIS, with 500x500m2 resolution. A statistical analysis of the NDVI histograms at consecutives 46 intervals of that area was applied to search for the best statistical distribution based on the maximum likelihood criteria. The results show that the normal distribution is not the optimal representation when IBI is available; the implications in the context of crop insurance are discussed (Martín-Sotoca, 2014). References Kolli N Rao. 2010. Index based Crop Insurance. Agriculture and Agricultural Science Procedia 1, 193-203. Martín-Sotoca, J.J. (2014) Estructura Espacial de la Sequía en Pastos y sus Aplicaciones en el Seguro Agrario. Master Thesis, UPM (In Spanish). Niemeyer, S., 2008: New drought indices. First Int. Conf. on Drought Management: Scientific and Technological Innovations, Zaragoza, Spain, Joint Research Centre of the European Commission. [Available online at http://www.iamz.ciheam.org/medroplan/zaragoza2008/Sequia2008/Session3/S.Niemeyer.pdf.] Xiaohui Deng, Barry J. Barnett, Gerrit Hoogenboom, Yingzhuo Yu and Axel Garcia y Garcia 2008. Alternative Crop Insurance Indexes. Journal of Agricultural and Applied Economics, 40(1), 223-237. Acknowledgements First author acknowledges the Research Grant obtained from CEIGRAM in 2014

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 in other areas is expected to lead to better preparedness and mitigation-oriented management of droughts.

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

NASA Astrophysics Data System (ADS)

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

2016-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

a Brazilian Vulnerability Index to Natural Disasters of Drought - in the Context of Climate Change

NASA Astrophysics Data System (ADS)

Camarinha, P. I., Sr.; Debortoli, N. S.; Hirota, M.

2015-12-01

Droughts are characterized as one of the main types of natural disasters that occur in Brazil. During the 1991-2012, droughts affected more than 14 million Brazilians, so that the concern for the following decades is about the potential impacts triggered by climate change. To analyze the vulnerability of the Brazilian municipalities to drought disasters, we have assessed the effects of climate change to droughts until the end of 21th century. A composite index was created based on three different dimensions: i) Exposure, represented by climate anomalies related to the drought process, such as changes in accumulated rainfall averages, interannual variability of rainfall, and the frequency and magnitude of severe droughts (measured by the Standardized Precipitation-Evapotranspiration Index); ii) Sensitivity, encompassing socioeconomic, demographic, land use and water management data; iii) Adaptive Capacity, consisting of socioeconomic and institutional data from Brazilian municipalities, such as the Human Development Index (HDI), social inequality (Gini index) and illiteracy rate. The climate variables used in this study are results from simulations of the Regional Climate Model Eta (with a downscaling of 20km spatial resolution) nested with two global climate models (HadGEM ES and MIROC 5) and was provided by National Institute for Space Research. The baseline period was 1961-1990 and future periods was 2011-2040; 2041-2070 and 2071-2099. For the simulations of future climate it was used the 4.5 and 8.5 IPCC/AR5 RCP (Representative Concentration Pathways) scenarios. All variables used in this study was handled, exploited and related in a Geographic Information System (GIS). The methodology allowed the identification of vulnerability hotspots, the targeting of adaptation strategies and the development of public policy to minimize the potential impacts of future droughts. The final results (see attached image) indicate that the most vulnerable regions are located in the Midwest, in the northeastern Brazilian semi-arid and also on western Amazon.

A conceptual prediction model for seasonal drought processes using atmospheric and oceanic standardized anomalies: application to regional drought processes in China

NASA Astrophysics Data System (ADS)

Liu, Zhenchen; Lu, Guihua; He, Hai; Wu, Zhiyong; He, Jian

2018-01-01

Reliable drought prediction is fundamental for water resource managers to develop and implement drought mitigation measures. Considering that drought development is closely related to the spatial-temporal evolution of large-scale circulation patterns, we developed a conceptual prediction model of seasonal drought processes based on atmospheric and oceanic standardized anomalies (SAs). Empirical orthogonal function (EOF) analysis is first applied to drought-related SAs at 200 and 500 hPa geopotential height (HGT) and sea surface temperature (SST). Subsequently, SA-based predictors are built based on the spatial pattern of the first EOF modes. This drought prediction model is essentially the synchronous statistical relationship between 90-day-accumulated atmospheric-oceanic SA-based predictors and SPI3 (3-month standardized precipitation index), calibrated using a simple stepwise regression method. Predictor computation is based on forecast atmospheric-oceanic products retrieved from the NCEP Climate Forecast System Version 2 (CFSv2), indicating the lead time of the model depends on that of CFSv2. The model can make seamless drought predictions for operational use after a year-to-year calibration. Model application to four recent severe regional drought processes in China indicates its good performance in predicting seasonal drought development, despite its weakness in predicting drought severity. Overall, the model can be a worthy reference for seasonal water resource management in China.

Pan-European comparison of candidate distributions for climatological drought indices, SPI and SPEI

NASA Astrophysics Data System (ADS)

Stagge, James; Tallaksen, Lena; Gudmundsson, Lukas; Van Loon, Anne; Stahl, Kerstin

2013-04-01

Drought indices are vital to objectively quantify and compare drought severity, duration, and extent across regions with varied climatic and hydrologic regimes. The Standardized Precipitation Index (SPI), a well-reviewed meterological drought index recommended by the WMO, and its more recent water balance variant, the Standardized Precipitation-Evapotranspiration Index (SPEI) both rely on selection of univariate probability distributions to normalize the index, allowing for comparisons across climates. The SPI, considered a universal meteorological drought index, measures anomalies in precipitation, whereas the SPEI measures anomalies in climatic water balance (precipitation minus potential evapotranspiration), a more comprehensive measure of water availability that incorporates temperature. Many reviewers recommend use of the gamma (Pearson Type III) distribution for SPI normalization, while developers of the SPEI recommend use of the three parameter log-logistic distribution, based on point observation validation. Before the SPEI can be implemented at the pan-European scale, it is necessary to further validate the index using a range of candidate distributions to determine sensitivity to distribution selection, identify recommended distributions, and highlight those instances where a given distribution may not be valid. This study rigorously compares a suite of candidate probability distributions using WATCH Forcing Data, a global, historical (1958-2001) climate dataset based on ERA40 reanalysis with 0.5 x 0.5 degree resolution and bias-correction based on CRU-TS2.1 observations. Using maximum likelihood estimation, alternative candidate distributions are fit for the SPI and SPEI across the range of European climate zones. When evaluated at this scale, the gamma distribution for the SPI results in negatively skewed values, exaggerating the index severity of extreme dry conditions, while decreasing the index severity of extreme high precipitation. This bias is particularly notable for shorter aggregation periods (1-6 months) during the summer months in southern Europe (below 45° latitude), and can partially be attributed to distribution fitting difficulties in semi-arid regions where monthly precipitation totals cluster near zero. By contrast, the SPEI has potential for avoiding this fitting difficulty because it is not bounded by zero. However, the recommended log-logistic distribution produces index values with less variation than the standard normal distribution. Among the alternative candidate distributions, the best fit distribution and the distribution parameters vary in space and time, suggesting regional commonalities within hydroclimatic regimes, as discussed further in the presentation.

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

NASA Astrophysics Data System (ADS)

Crockett, J.; Westerling, A. L.

2016-12-01

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

Drought variability in six catchments in the UK

NASA Astrophysics Data System (ADS)

Kwok-Pan, Chun; Onof, Christian; Wheater, Howard

2010-05-01

Drought is fundamentally related to consistent low precipitation levels. Changes in global and regional drought patterns are suggested by numerous recent climate change studies. However, most of the climate change adaptation measures are at a catchment scale, and the development of a framework for studying persistence in precipitation is still at an early stage. Two stochastic approaches for modelling drought severity index (DSI) are proposed to investigate possible changes in droughts in six catchments in the UK. They are the autoregressive integrated moving average (ARIMA) and the generalised linear model (GLM) approach. Results of ARIMA modelling show that mean sea level pressure and possibly the North Atlantic Oscillation (NAO) index are important climate variables for short term drought forecasts, whereas relative humidity is not a significant climate variable despite its high correlation with the DSI series. By simulating rainfall series, the generalised linear model (GLM) approach can provide the probability density function of the DSI. GLM simulations indicate that the changes in the 10th and 50th quantiles of drought events are more noticeable than in the 90th extreme droughts. The possibility of extending the GLM approach to support risk-based water management is also discussed.

Impacts of climate change on vegetation, hydrological and socio-economic droughts in a transitional wet-to-dry Mediterranean region

NASA Astrophysics Data System (ADS)

Nunes, João Pedro; Pulquério, Mário; Grosso, Nuno; Duarte Santos, Filipe; João Cruz, Maria

2015-04-01

The Tagus river basin is located in a transitional region between humid and semi-arid climate. The lower part of the basin is a strategic source of water for Portugal, providing water for agricultural irrigation, hydropower generation, and domestic water supplies for over 4 million people. Climate change in this region is expected to lead to higher temperatures and lower rainfall, therefore increasing climatic aridity. In this transitional region, this could lead to an increased frequency of severe droughts, threatening climatic support for current agricultural and forestry practices, as well as the sustainability of domestic water supplies. This work evaluated the impacts of climate change on drought frequency and severity for the Portuguese part of the Tagus river basin. Climate change scenarios for 2010-2100 (A2 greenhouse emission scenarios) were statistically downscaled for the study area. They were evaluated with the Soil and Water Assessment Tool (SWAT) eco-hydrological model, which simulated vegetation water demand and drought stress, soil water availability, irrigation abstraction, streamflow, reservoir storage and groundwater recharge. Water inflows from Spain were estimated using an empirical climate-based model. Drought occurrence and severity was analyzed in terms of: * meteorological drought, based on (i) the Standardized Precipitation Index and (ii) the Aridity Index; * vegetation/agricultural drought, based on plant water stress; * hydrological drought, based on (i) streamflow rates and (ii) reservoir storage; * socio-economic drought, based on (i) the capacity of the main reservoir in the system (Castelo de Bode) to sustain hydropower and domestic supplies, and (ii) the rate of groundwater extraction vs. irrigation demands for the cultures located in the intensive cultivation regions of the Lezírias near the Tagus estuary. The results indicate a trend of increasing frequency and severity of most drought types during the XXIst century, with a noticeable increase in the latter decades. The exceptions are agricultural droughts for annual crops, which appear to benefit from a milder and rainier winter; and domestic water supplies, which are not threatened in any scenario as long as they are prioritized over other water uses.

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

NASA Astrophysics Data System (ADS)

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

2008-12-01

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

Statistical attribution of mid-term droughts in central Europe

NASA Astrophysics Data System (ADS)

Mikšovský, Jiří; Trnka, Miroslav; Brázdil, Rudolf

2017-04-01

Occurrence and intensity of meteorological droughts are determined by a number of factors, both anthropogenic and natural. Besides the trend-like components, often attributable to local or global man-induced changes to the climate system, manifestations of internal climate oscillatory modes are also of great importance in establishing the hydrological regime. In this presentation, we focus on identification and quantification of factors responsible for central European drought variability at seasonal time scales. Using multivariable regression analysis applied to predictands reflecting various definitions of meteorological droughts (based on Standardized Precipitation Index, Standardized Precipitation Evapotranspiration Index and Palmer's Z-index, over the 1883-2010 period), components attributable to external and internal climate-forming agents are extracted and evaluated with regard to their statistical significance. Our results confirm presence of strong links of central European droughts to the anthropogenic radiative forcing and to the phase of the North Atlantic Oscillation, but also existence of connections to the climate oscillations originating from the Pacific area. In this context, we demonstrate that prominence of components related to the phase of the Pacific Decadal Oscillation generally surpasses that of El Niño - Southern Oscillation, although the related transfer mechanisms still remain unclear. Finally, it is shown that noteworthy deviations from linearity exist in some of the drought responses, particularly for the effects of the North Atlantic Oscillation.

Assessment of the Standardized Precipitation Index (SPI) in Tegal City, Central Java, Indonesia

NASA Astrophysics Data System (ADS)

Pramudya, Y.; Onishi, T.

2018-03-01

One of the adverse impacts of climate change is drought, which occurs more frequently in Tegal city, Indonesia. The application of drought index analysis is useful for drought assessment to consider adaptation and mitigation method in order to deal with climate change. By figuring out the level and duration of the drought. In order to analyze drought in the specific area, Standardized Precipitation Index (SPI) is an index to quantify the rainfall deficit for multiple timescales. In 2015, Indonesia experienced severe drought, which has not been analyzed, yet. Thus, it is important to assess a quantitative evaluation of the drought condition. The study shows that from all deficit periods, the most severe drought in duration and peak took place in 2015, with each drought index as follows: 1 month deficit or SPI-1 (-3.11) in 1985 (-2.51) in 2015, 3 month deficit or SPI-3 (-2.291) in 1995 (-1.82) in 2015, 6 month deficit or SPI-6 (-2.40) in 1997 and (-1.84) in 2015, 9 month deficit or SPI-9 (-1.12) in 2015, 12 month deficit or SPI-12 (-1.19) in 2015. The result underlines the potential that SPI exhibits in drought identification and the use of the rainfall strongly linked to drought relief policy and measure implementation in Tegal city.

Bivariate drought frequency analysis using the copula method

NASA Astrophysics Data System (ADS)

Mirabbasi, Rasoul; Fakheri-Fard, Ahmad; Dinpashoh, Yagob

2012-04-01

Droughts are major natural hazards with significant environmental and economic impacts. In this study, two-dimensional copulas were applied to the analysis of the meteorological drought characteristics of the Sharafkhaneh gauge station, located in the northwest of Iran. Two major drought characteristics, duration and severity, as defined by the standardized precipitation index, were abstracted from observed drought events. Since drought duration and severity exhibited a significant correlation and since they were modeled using different distributions, copulas were used to construct the joint distribution function of the drought characteristics. The parameter of copulas was estimated using the method of the Inference Function for Margins. Several copulas were tested in order to determine the best data fit. According to the error analysis and the tail dependence coefficient, the Galambos copula provided the best fit for the observed drought data. Some bivariate probabilistic properties of droughts, based on the derived copula-based joint distribution, were also investigated. These probabilistic properties can provide useful information for water resource planning and management.

Quantile regression and clustering analysis of standardized precipitation index in the Tarim River Basin, Xinjiang, China

NASA Astrophysics Data System (ADS)

Yang, Peng; Xia, Jun; Zhang, Yongyong; Han, Jian; Wu, Xia

2017-11-01

Because drought is a very common and widespread natural disaster, it has attracted a great deal of academic interest. Based on 12-month time scale standardized precipitation indices (SPI12) calculated from precipitation data recorded between 1960 and 2015 at 22 weather stations in the Tarim River Basin (TRB), this study aims to identify the trends of SPI and drought duration, severity, and frequency at various quantiles and to perform cluster analysis of drought events in the TRB. The results indicated that (1) both precipitation and temperature at most stations in the TRB exhibited significant positive trends during 1960-2015; (2) multiple scales of SPIs changed significantly around 1986; (3) based on quantile regression analysis of temporal drought changes, the positive SPI slopes indicated less severe and less frequent droughts at lower quantiles, but clear variation was detected in the drought frequency; and (4) significantly different trends were found in drought frequency probably between severe droughts and drought frequency.

Response of Main Maize Varieties to Water Stress and Comprehensive Evaluation in Hebei Province

NASA Astrophysics Data System (ADS)

Yue, Haiwang; Chen, Shuping; Bu, Junzhou; Wei, Jianwei; Peng, Haicheng; Li, Yuan; Li, Chunjie; Xie, Junliang

2018-01-01

Drought is a serious threat to maize production in Hebei province. Planting drought resistant maize varieties is an effective measure to solve drought in arid and less rain areas. Drought resistance in maize is controlled by many genes, and multiple indexes should be used for comprehensive evaluation (Campos H et al.2004). In the arid rain shed, using 34 maize varieties to promote crop production compared to the drought resistance test. The experiment was conducted with two treatments of drought stress (irrigation only at seedling stage) and normal irrigation, and 12 agronomic traits related to drought resistance of maize were determined. The results showed that drought had significant effects on maize yield and main agronomic characters. Under drought stress, plant height, ear length, bare tip, ear row number, row grains, 1000-kernel weight, ASI index can be used as identification index of drought resistance of maize in different period. The results indicated that the variety with strong drought resistance is Zhongdi175, the worst drought resistance is Woyu964.

Assessing the evolution of soil moisture and vegetation conditions during the 2012 United States flash drought

USGS Publications Warehouse

Otkin, Jason A.; Anderson, Martha C.; Hain, Christopher; Svoboda, Mark; Johnson, David; Mueller, Richard; Tadesse, Tsegaye; Wardlow, Brian D.; Brown, Jesslyn

2016-01-01

This study examines the evolution of several model-based and satellite-derived drought metrics sensitive to soil moisture and vegetation conditions during the extreme flash drought event that impacted major agricultural areas across the central U.S. during 2012. Standardized anomalies from the remote sensing based Evaporative Stress Index (ESI) and Vegetation Drought Response Index (VegDRI) and soil moisture anomalies from the North American Land Data Assimilation System (NLDAS) are compared to the United States Drought Monitor (USDM), surface meteorological conditions, and crop and soil moisture data compiled by the National Agricultural Statistics Service (NASS).Overall, the results show that rapid decreases in the ESI and NLDAS anomalies often preceded drought intensification in the USDM by up to 6 wk depending on the region. Decreases in the ESI tended to occur up to several weeks before deteriorations were observed in the crop condition datasets. The NLDAS soil moisture anomalies were similar to those depicted in the NASS soil moisture datasets; however, some differences were noted in how each model responded to the changing drought conditions. The VegDRI anomalies tracked the evolution of the USDM drought depiction in regions with slow drought development, but lagged the USDM and other drought indicators when conditions were changing rapidly. Comparison to the crop condition datasets revealed that soybean conditions were most similar to ESI anomalies computed over short time periods (2–4 wk), whereas corn conditions were more closely related to longer-range (8–12 wk) ESI anomalies. Crop yield departures were consistent with the drought severity depicted by the ESI and to a lesser extent by the NLDAS and VegDRI datasets.

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 by optimising the weights.

Towards drought risk mapping on a pan-European scale

NASA Astrophysics Data System (ADS)

Blauhut, Veit; Gudmundsson, Lukas; Stahl, Kerstin; Seneviratne, Sonia

2014-05-01

Drought is a very complex and multifarious natural hazard, which causes a variety of direct and indirect environmental and socio-economic impacts. For the last 30 years, droughts in Europe caused over 100 billion Euros of losses from impacts in various sectors e.g. agriculture, water quality or energy production. Despite the apparent importance of this hazard observed pan-European drought impacts have not yet been quantitatively related to the most important climatological drivers. Fundamentally, a common approach to describe drought risk on a pan-European scale is still missing. This contribution presents an approach for linking climatological drought indices with observed drought impacts at the European scale. Standardized precipitation index (SPI) and standardized precipitation and evapotranspiration index (SPEI) for different time scales were calculated based on E-OBS data and are used to describe the drought hazard. Data from the European Drought Impact Inventory (EDII) compiled by the EU FP7 Drought R&SPI (Fostering European Drought Research and Science-Policy Interfacing) project are used as a proxy for multi-sectorial (impact categories) vulnerability following the assumption that a reported impact reflects a region's vulnerability to the hazard. Drought risk is then modelled statistically by applying logistic regression to estimate the probability of impact report occurrence as a function of SPI and SPEI. This approach finally allows to map the probability of drought impact occurrence on a year by year basis. The emerging patterns compare well to many known European drought events. Such maps may become an essential component of Drought Risk Management to foster resilience for this hazard at the large scale.

Current and future droughts in the Southeastern Mediterranean

NASA Astrophysics Data System (ADS)

Törnros, Tobias; Menzel, Lucas

2016-04-01

The southeastern Mediterranean region (i.e., Israel, Palestine, Jordan and neighboring countries) increasingly suffers significant water stress. The semi-arid to arid conditions with low precipitation amounts, high temperatures and strong interannual climate variability recurrently trigger drought conditions. However, the complex political situation, showing a low degree of mutual cooperation, favors an unsustainable use of water resources and no long-term, cross-boundary water management plan exists. In order to address the drought conditions under current and future climates in this region, the Standardized Precipitation-Evaporation Index (SPEI) was applied. In the first step, the SPEI was derived from spatially interpolated monthly precipitation and temperature data at multiple timescales: accumulated precipitation and monthly mean temperature were considered over a different number of consecutive months. To investigate the performance of the drought index, correlation analyses were conducted with simulated soil moisture and the Normalized Difference Vegetation Index (NDVI) obtained from remote sensing. A comparison with the Standardized Precipitation Index (SPI), i.e., a drought index that does not incorporate temperature, was also conducted. The results show that the choice of the SPEI/SPI timescale is crucial. In our study, the 6-month SPEI has the highest correlation with simulated soil moisture and best explains the interannual variation of the monthly NDVI. Although not extensively addressed, the SPI performs almost just as well and could be applied if temperature data are not available. In the second step, the 6-month SPEI was derived from three climate projections based on the IPCC emission scenario A1B. When comparing the period 2031-2060 with 1961-1990, it is shown that the percentage of time with moderate, severe and extreme drought conditions is projected to strongly increase for all scenarios. Since agriculture is by far the most water demanding sector in the region, the impact of drought on agriculture was addressed. For this, the irrigation water demand during certain drought years was simulated with a hydrological model on a spatial resolution of 1 km. A large increase in the demand for irrigation water was simulated, showing that the agricultural sector is expected to become even more vulnerable to drought in the future.

Effective Use of Water and Increased Dry Matter Partitioned to Grain Contribute to Yield of Common Bean Improved for Drought Resistance

PubMed Central

Polania, Jose A.; Poschenrieder, Charlotte; Beebe, Stephen; Rao, Idupulapati M.

2016-01-01

Common bean (Phaseolus vulgaris L.) is the most important food legume in the diet of poor people in the tropics. Drought causes severe yield loss in this crop. Identification of traits associated with drought resistance contributes to improving the process of generating bean genotypes adapted to these conditions. Field studies were conducted at the International Center for Tropical Agriculture (CIAT), Palmira, Colombia, to determine the relationship between grain yield and different parameters such as effective use of water (EUW), canopy biomass, and dry partitioning indices (pod partitioning index, harvest index, and pod harvest index) in elite lines selected for drought resistance over the past decade. Carbon isotope discrimination (CID) was used for estimation of water use efficiency (WUE). The main objectives were: (i) to identify specific morpho-physiological traits that contribute to improved resistance to drought in lines developed over several cycles of breeding and that could be useful as selection criteria in breeding; and (ii) to identify genotypes with desirable traits that could serve as parents in the corresponding breeding programs. A set of 36 bean genotypes belonging to the Middle American gene pool were evaluated under field conditions with two levels of water supply (irrigated and drought) over two seasons. Eight bean lines (NCB 280, NCB 226, SEN 56, SCR 2, SCR 16, SMC 141, RCB 593, and BFS 67) were identified as resistant to drought stress. Resistance to terminal drought stress was positively associated with EUW combined with increased dry matter partitioned to pod and seed production and negatively associated with days to flowering and days to physiological maturity. Differences in genotypic response were observed between grain CID and grain yield under irrigated and drought stress. Based on phenotypic differences in CID, leaf stomatal conductance, canopy biomass, and grain yield under drought stress, the lines tested were classified into two groups, water savers and water spenders. Pod harvest index could be a useful selection criterion in breeding programs to select for drought resistance in common bean. PMID:27242861

Comparison of drought events detected by SPI calculated from different historical precipitation data sets - case study from Southern Alps

NASA Astrophysics Data System (ADS)

Brencic, M.; Hictaler, J.

2012-04-01

During recent years substantial efforts were directed toward the reconstruction of past meteorological data sets of precipitation, air temperature, air pressure and sunshine. In Alpine space of Europe long tradition of meteorological data monitoring exist starting with the first modern measurements in late 18th century. However, older data were obtained under very different conditions, standards and quality. Consequently direct comparison between data sets of different observation points is not possible. Several methods defined as data homogenisation procedures were developed intended to enable comparison of data from different observation points and sources. In spite of the fact that homogenisation procedures are scientifically agreed final result represented as homogenised data series depends on the ability and approach of the interpreters. Well know data set from the Greater Alpine region based on the common homogenisation procedure is HISTALP data series. However, HISTALP data set is not the only available homogenised data set in the region. Local agencies responsible for meteorological observations (e.g. in Slovenia Environmental Agency of Slovenia - ARSO) perform their own homogenisation procedures. Because more detailed information about measuring procedures and locations for the particular stations is available for them one can expect differences between homogenised data sets. Longer meteorological data sets can be used to detect past drought events of various magnitudes. They can help to discern past droughts and their characteristics. A very frequently used meteorological drought index is standardized precipitation index - SPI. The nature of SPI is designed to detect events of low frequency. With the help of this index periods of extremely low precipitation can be defined. It is usually based on monthly amount of precipitation where cumulative precipitation amount for the particular time period is calculated. During the calculation of SPI with a time series of monthly precipitation data for a location can calculate the SPI for any month in the record for the previous i months where i=1,2,3, …, 12, …, 24, …. 48, … depending upon the time scale of the interest. A 3 month SPI index is usually used for a short-term or seasonal drought index, a 12 month SPI is used for an intermediate term drought index, and a 48 month SPI is used for a long term drought index. In the paper results of SPI calculations are presented for the precipitation stations in the region of the Southern Alps for the last 200 years. Compared are results of differently homogenised data sets for the same observation points. We have performed comparison of homogenised data sets between HISTALP and ARSO data base. For the period after World War II when reliable precipitation measurements are available comparison was performed also between raw data series and homogenised data series. Differences between calculated form short term SPI (from 1 to 6 months) are small and don't influence the interpretation of short term drought appearance. With the prolonged length of SPI differences between calculated values rise and influence the detection of longer term drought appearance. It can be also illustrated that differences among parameters of model distribution (gamma distribution) are larger for longer SPI than for shorter SPI. It can be empirically concluded that homogenisation procedure of precipitation data sets can importantly influence the SPI values and has impact on conclusions about long term drought appearance.

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

PubMed Central

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

2018-01-01

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

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

PubMed

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

2018-04-23

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

Documentary and instrumental-based drought indices for the Czech Lands back to AD 1501

NASA Astrophysics Data System (ADS)

Brázdil, Rudolf; Dobrovolný, Petr; Trnka, Miroslav; Büntgen, Ulf; Řezníčková, Ladislava; Kotyza, Oldřich; Valášek, Hubert; Štěpánek, Petr

2016-04-01

This study addresses the reconstruction of four slightly different drought indices in the Czech Lands (recent Czech Republic) back to 1501 AD. Reconstructed monthly temperatures for central Europe that are representative for the Czech territory, together with reconstructed seasonal precipitation totals from the same area, are used to calculate monthly, seasonal and annual drought indices (SPI, SPEI, Z-index, and PDSI). The resulting time-series reflect interannual-to multi-decadal drought variability. The driest episodes cluster around the beginning and end of the 18th century, while 1540 emerges as a particularly dry extreme year. The temperature-driven dryness of the past three decades is well captured by SPEI, Z-index and PDSI, whereas precipitation totals show no significant trend during this period (as reflected in SPI). Data and methodological uncertainty associated with Czech drought indices, as well as their position in a greater European context, are critically outlined. Further discussion is devoted to comparison with fir tree-rings from southern Moravia and a spatial subset of the "Old World Drought Atlas" (OWDA), which reveals significant correlation coefficients, of around 0.40 and 0.50, respectively. This study introduces a new documentary-based approach for the robust extension of standardized drought indices back into pre-instrumental times, which we also believe has great potential in other parts of the world where high-resolution paleoclimatic insight remains as yet limited.

Drought Early Warning and Agro-Meteorological Risk Assessment using Earth Observation Rainfall Datasets and Crop Water Budget Modelling

NASA Astrophysics Data System (ADS)

Tarnavsky, E.

2016-12-01

The water resources satisfaction index (WRSI) model is widely used in drought early warning and food security analyses, as well as in agro-meteorological risk management through weather index-based insurance. Key driving data for the model is provided from satellite-based rainfall estimates such as ARC2 and TAMSAT over Africa and CHIRPS globally. We evaluate the performance of these rainfall datasets for detecting onset and cessation of rainfall and estimating crop production conditions for the WRSI model. We also examine the sensitivity of the WRSI model to different satellite-based rainfall products over maize growing regions in Tanzania. Our study considers planting scenarios for short-, medium-, and long-growing cycle maize, and we apply these for 'regular' and drought-resistant maize, as well as with two different methods for defining the start of season (SOS). Simulated maize production estimates are compared against available reported production figures at the national and sub-national (province) levels. Strengths and weaknesses of the driving rainfall data, insights into the role of the SOS definition method, and phenology-based crop yield coefficient and crop yield reduction functions are discussed in the context of space-time drought characteristics. We propose a way forward for selecting skilled rainfall datasets and discuss their implication for crop production monitoring and the design and structure of weather index-based insurance products as risk transfer mechanisms implemented across scales for smallholder farmers to national programmes.

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 between meteorological drought indicators and remotely sensed vegetation stress at the EU NUTS3 region level revealed a high correlation between the two types of indicators for many regions; however some spatial variability was observed in (i) strength of correlation, (ii) performance of SPI versus SPEI, and (iii) best linked SPI/SPEI time scale. We additionally explored whether geographic properties like climate, soil texture, land use, and location explain the observed spatial patterns. Our study revealed that climatically dryer areas (water limited) showed high correlations between SPI/SPEI and vegetation stress, whereas the wettest parts of Europe (radiation limited regions) showed negative correlations especially for short accumulation periods, suggesting that for these regions, short droughts could actually be beneficial for vegetation growth. These findings suggest that relying solely on meteorological indicators for agricultural risk assessment in some regions might be inadequate. Overall, such information may help to tailor agricultural drought M&EW systems to specific regions.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Middle-term Metropolitan Water Availability Index Assessment Based on Synergistic Potentials of Multi-sensor Data

EPA Science Inventory

The impact of recent drought and water pollution episodes results in an acute need to project future water availability to assist water managers in water utility infrastructure management within many metropolitan regions. Separate drought and water quality indices previously deve...

Pasture Drought Insurance Based on NDVI and SAVI

NASA Astrophysics Data System (ADS)

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

2012-04-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Atmospheric rivers as drought busters on the U.S. west coast

USGS Publications Warehouse

Dettinger, Michael D.

2013-01-01

Atmospheric rivers (ARs) have, in recent years, been recognized as the cause of the large majority of major floods in rivers all along the U.S. West Coast and as the source of 30%–50% of all precipitation in the same region. The present study surveys the frequency with which ARs have played a critical role as a common cause of the end of droughts on the West Coast. This question was based on the observation that, in most cases, droughts end abruptly as a result of the arrival of an especially wet month or, more exactly, a few very large storms. This observation is documented using both Palmer Drought Severity Index and 6-month Standardized Precipitation Index measures of drought occurrence for climate divisions across the conterminous United States from 1895 to 2010. When the individual storm sequences that contributed most to the wet months that broke historical West Coast droughts from 1950 to 2010 were evaluated, 33%–74% of droughts were broken by the arrival of landfalling AR storms. In the Pacific Northwest, 60%–74% of all persistent drought endings have been brought about by the arrival of AR storms. In California, about 33%–40% of all persistent drought endings have been brought about by landfalling AR storms, with more localized low pressure systems responsible for many of the remaining drought breaks.

Exploiting teleconnection indices for probabilistic forecasting of drought class transitions in Sicily region (Italy)

NASA Astrophysics Data System (ADS)

Bonaccorso, Brunella; Cancelliere, Antonino

2015-04-01

In the present study two probabilistic models for short-medium term drought forecasting able to include information provided by teleconnection indices are proposed and applied to Sicily region (Italy). Drought conditions are expressed in terms of the Standardized Precipitation-Evapotranspiration Index (SPEI) at different aggregation time scales. More specifically, a multivariate approach based on normal distribution is developed in order to estimate: 1) on the one hand transition probabilities to future SPEI drought classes and 2) on the other hand, SPEI forecasts at a generic time horizon M, as functions of past values of SPEI and the selected teleconnection index. To this end, SPEI series at 3, 4 and 6 aggregation time scales for Sicily region are extracted from the Global SPEI database, SPEIbase , available at Web repository of the Spanish National Research Council (http://sac.csic.es/spei/database.html), and averaged over the study area. In particular, SPEIbase v2.3 with spatial resolution of 0.5° lat/lon and temporal coverage between January 1901 and December 2013 is used. A preliminary correlation analysis is carried out to investigate the link between the drought index and different teleconnection patterns, namely: the North Atlantic Oscillation (NAO), the Scandinavian (SCA) and the East Atlantic-West Russia (EA-WR) patterns. Results of such analysis indicate a strongest influence of NAO on drought conditions in Sicily with respect to other teleconnection indices. Then, the proposed forecasting methodology is applied and the skill in forecasting of the proposed models is quantitatively assessed through the application of a simple score approach and of performance indices. Results indicate that inclusion of NAO index generally enhance model performance thus confirming the suitability of the models for short- medium term forecast of drought conditions.

Integrated Mapping of Drought-Impacted Areas in the Sierra-Nevada Foothills Region of California Using Landsat Imagery

NASA Astrophysics Data System (ADS)

Rao, M.

2014-12-01

Drought is a natural disaster with serious implications to environmental, social and economic well-being at local, regional and global scales. In its third year, California's drought condition has seriously impacted not just the agricultural sector, but also the natural resources sector including forestry, wildlife, and fisheries. As of July 15, 2014, the National Weather Service drought monitor shows 81% of California in the category of extreme drought. As future predictions of drought and fire severity become more real in California, there is an increased awareness to pursue innovative and cost-effective solutions that are based on silvicultural treatments and controlled burns to improve forest health and reduce the risk of high-severity wildfires. The main goal of this study is to develop a GIS map of the drought-impacted region of northern and central California using remote sensing data. Specifically, based on a geospatial database for the study region, Landsat imagery in conjunction with field and ancillary data will be analyzed using a combination of supervised and unsupervised classification techniques in addition to spectral indices such as the Modified Perpendicular Drought Index (MPDI). This spectral index basically scales the line perpendicular to the soil line defined in the Red-NIR feature space in conjunction with added information about vegetative fraction derived using NDVI. The image processing will be conducted for two time periods (2001 and 2014) to characterize the severity of the drought. In addition to field data, data collected by state agencies including calforests.org will be used in the classification and accuracy assessment procedures. Visual assessment using high-resolution imagery such as NAIP will be used to further refine the spatial maps. The drought severity maps produced will greatly facilitate site-specific planning efforts aimed at implementing resource management decisions.

Exacerbated degradation and desertification of grassland in Central Asia

NASA Astrophysics Data System (ADS)

Zhang, G.; Xiao, X.; Biradar, C. M.; Dong, J.; Zhou, Y.; Qin, Y.; Zhang, Y.; Liu, F.; Ding, M.; Thomas, R. J.

2016-12-01

Grassland desertification is a complex process, including both state conversion (e.g., grasslands to deserts) and gradual within-state change (e.g., greenness dynamics). Existing studies generally did not separate the two components and analyzed them based on time series vegetation indices, which however cannot provide a clear and comprehensive picture for desertification. Here we proposed a desertification zone classification-based grassland degradation strategy to detect the grassland desertification process in Central Asia. First, annual spatially explicit maps of grasslands and deserts were generated to track the conversion between grasslands and deserts. The results showed that 13 % of grasslands were converted to deserts from 2000 to 2014, with an increasing desertification trend northward in the latitude range of 43-48°N. Second, a fragile and unstable Transitional zone was identified in southern Kazakhstan based on desert frequency maps. Third, gradual vegetation dynamics during the thermal growing season (EVITGS) were investigated using linear regression and Mann-Kendall approaches. The results indicated that grasslands generally experienced widespread degradation in Central Asia, with an additional hotspot identified in the northern Kazakhstan. Finally, attribution analyses of desertification were conducted by correlating vegetation dynamics with three different drought indices (Palmer Drought Severity Index (PDSI), Standardized Precipitation Index (SPI), and Drought Severity Index (DSI)), precipitation, and temperature, and showed that grassland desertification was exacerbated by droughts, and persistent drought was the main factor for grassland desertification in Central Asia. This study provided essential information for taking practical actions to prevent the further desertification and targeting right spots for better intervention to combat the land degradation in the region.

The Gaussian copula model for the joint deficit index for droughts

NASA Astrophysics Data System (ADS)

Van de Vyver, H.; Van den Bergh, J.

2018-06-01

The characterization of droughts and their impacts is very dependent on the time scale that is involved. In order to obtain an overall drought assessment, the cumulative effects of water deficits over different times need to be examined together. For example, the recently developed joint deficit index (JDI) is based on multivariate probabilities of precipitation over various time scales from 1- to 12-months, and was constructed from empirical copulas. In this paper, we examine the Gaussian copula model for the JDI. We model the covariance across the temporal scales with a two-parameter function that is commonly used in the specific context of spatial statistics or geostatistics. The validity of the covariance models is demonstrated with long-term precipitation series. Bootstrap experiments indicate that the Gaussian copula model has advantages over the empirical copula method in the context of drought severity assessment: (i) it is able to quantify droughts outside the range of the empirical copula, (ii) provides adequate drought quantification, and (iii) provides a better understanding of the uncertainty in the estimation.

Assessment of MODIS-derived indices (2001-2013) to drought across Taiwan's forests

NASA Astrophysics Data System (ADS)

Chang, Chung-Te; Wang, Hsueh-Ching; Huang, Cho-ying

2018-05-01

Tropical and subtropical ecosystems, the largest terrestrial carbon pools, are very susceptible to the variability of seasonal precipitation. However, the assessment of drought conditions in these regions is often overlooked due to the preconceived notion of the presence of high humidity. Drought indices derived from remotely sensed imagery have been commonly used for large-scale monitoring, but feasibility of drought assessment may vary across regions due to climate regimes and local biophysical conditions. Therefore, this study aims to evaluate the feasibility of 11 commonly used MODIS-derived vegetation/drought index in the forest regions of Taiwan through comparison with the station-based standardized precipitation index with a 3-month time scale (SPI3). The drought indices were further transformed (standardized anomaly, SA) to make them better delineate the spatiotemporal variations of drought conditions. The results showed that the Normalized Difference Infrared Index utilizing the near-infrared and shortwave infrared bands (NDII6) may be more superior to other indices in delineating drought patterns. Overall, the NDII6 SA-SPI3 pair yielded the highest correlation (mean r ± standard deviation = 0.31 ± 0.13) and was most significant in central and south Taiwan ( r = 0.50-0.90) during the cold, dry season (January and April). This study illustrated that the NDII6 is suitable to delineate drought conditions in a relatively humid region. The results suggested the better performance of the NDII6 SA-SPI3 across the high climate gradient, especially in the regions with dramatic interannual amplifications of rainfall. This synthesis was conducted across a wide bioclimatic gradient, and the findings could be further generalized to a much broader geographical extent.

Assessment of MODIS-derived indices (2001-2013) to drought across Taiwan's forests

NASA Astrophysics Data System (ADS)

Chang, Chung-Te; Wang, Hsueh-Ching; Huang, Cho-ying

2017-12-01

Tropical and subtropical ecosystems, the largest terrestrial carbon pools, are very susceptible to the variability of seasonal precipitation. However, the assessment of drought conditions in these regions is often overlooked due to the preconceived notion of the presence of high humidity. Drought indices derived from remotely sensed imagery have been commonly used for large-scale monitoring, but feasibility of drought assessment may vary across regions due to climate regimes and local biophysical conditions. Therefore, this study aims to evaluate the feasibility of 11 commonly used MODIS-derived vegetation/drought index in the forest regions of Taiwan through comparison with the station-based standardized precipitation index with a 3-month time scale (SPI3). The drought indices were further transformed (standardized anomaly, SA) to make them better delineate the spatiotemporal variations of drought conditions. The results showed that the Normalized Difference Infrared Index utilizing the near-infrared and shortwave infrared bands (NDII6) may be more superior to other indices in delineating drought patterns. Overall, the NDII6 SA-SPI3 pair yielded the highest correlation (mean r ± standard deviation = 0.31 ± 0.13) and was most significant in central and south Taiwan (r = 0.50-0.90) during the cold, dry season (January and April). This study illustrated that the NDII6 is suitable to delineate drought conditions in a relatively humid region. The results suggested the better performance of the NDII6 SA-SPI3 across the high climate gradient, especially in the regions with dramatic interannual amplifications of rainfall. This synthesis was conducted across a wide bioclimatic gradient, and the findings could be further generalized to a much broader geographical extent.

Exploration of Use of Copulas in Analysing the Relationship between Precipitation and Meteorological Drought in Beijing, China

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

Fan, Linlin; Wang, Hongrui; Wang, Cheng

Drought risk analysis is essential for regional water resource management. In this study, the probabilistic relationship between precipitation and meteorological drought in Beijing, China, was calculated under three different precipitation conditions (precipitation equal to, greater than, or less than a threshold) based on copulas. The Standardized Precipitation Evapotranspiration Index (SPEI) was calculated based on monthly total precipitation and monthly mean temperature data. The trends and variations in the SPEI were analysed using Hilbert-Huang Transform (HHT) and Mann-Kendall (MK) trend tests with a running approach. The results of the HHT and MK test indicated a significant decreasing trend in the SPEI.more » The copula-based conditional probability indicated that the probability of meteorological drought decreased as monthly precipitation increased and that 10 mm can be regarded as the threshold for triggering extreme drought. From a quantitative perspective, when R ≤ mm, the probabilities of moderate drought, severe drought, and extreme drought were 22.1%, 18%, and 13.6%, respectively. This conditional probability distribution not only revealed the occurrence of meteorological drought in Beijing but also provided a quantitative way to analyse the probability of drought under different precipitation conditions. Furthermore, the results provide a useful reference for future drought prediction.« less

Exploration of Use of Copulas in Analysing the Relationship between Precipitation and Meteorological Drought in Beijing, China

DOE PAGES

Fan, Linlin; Wang, Hongrui; Wang, Cheng; ...

2017-05-16

Drought risk analysis is essential for regional water resource management. In this study, the probabilistic relationship between precipitation and meteorological drought in Beijing, China, was calculated under three different precipitation conditions (precipitation equal to, greater than, or less than a threshold) based on copulas. The Standardized Precipitation Evapotranspiration Index (SPEI) was calculated based on monthly total precipitation and monthly mean temperature data. The trends and variations in the SPEI were analysed using Hilbert-Huang Transform (HHT) and Mann-Kendall (MK) trend tests with a running approach. The results of the HHT and MK test indicated a significant decreasing trend in the SPEI.more » The copula-based conditional probability indicated that the probability of meteorological drought decreased as monthly precipitation increased and that 10 mm can be regarded as the threshold for triggering extreme drought. From a quantitative perspective, when R ≤ mm, the probabilities of moderate drought, severe drought, and extreme drought were 22.1%, 18%, and 13.6%, respectively. This conditional probability distribution not only revealed the occurrence of meteorological drought in Beijing but also provided a quantitative way to analyse the probability of drought under different precipitation conditions. Furthermore, the results provide a useful reference for future drought prediction.« less

Spatiotemporal characterization of current and future droughts in the High Atlas basins (Morocco)

NASA Astrophysics Data System (ADS)

Zkhiri, Wiam; Tramblay, Yves; Hanich, Lahoucine; Jarlan, Lionel; Ruelland, Denis

2018-02-01

Over the past decades, drought has become a major concern in Morocco due to the importance of agriculture in the economy of the country. In the present work, the standardized precipitation index (SPI) is used to monitor the evolution, frequency, and severity of droughts in the High Atlas basins (N'Fis, Ourika, Rhéraya, Zat, and R'dat), located south of Marrakech city. The spatiotemporal characterization of drought in these basins is performed by computing the SPI with precipitation spatially interpolated over the catchments. The Haouz plain, located downstream of these basins, is strongly dependent on water provided by the mountain ranges, as shown by the positive correlations between the normalized difference vegetation index (NDVI) in the plain and the 3, 6, and 12-month SPI in the High Atlas catchments. On the opposite, no significant correlations are found with piezometric levels of the Haouz groundwater due to intensified pumping for irrigation in the recent decades. A relative SPI index was computed to evaluate the climate change impacts on drought occurrence, based on the projected precipitation (2006-2100) from five high-resolution CORDEX regional climate simulations, under two emission scenarios (RCP 4.5 and RCP 8.5). These models show a decrease in precipitation towards the future up to - 65% compared to the historical period. In terms of drought events, the future projections indicate a strong increase in the frequency of SPI events below - 2, considered as severe drought condition.

Investigation of spatiotemporal relationship between dengue fever and drought

NASA Astrophysics Data System (ADS)

Lee, Chieh-Han; Yu, Hwa-Lung

2016-04-01

Dengue Fever is a vector-borne disease that is transmitted between human and mosquitos in tropical and sub-tropical regions. Previous studies have found significant relationship between the epidemic of dengue cases and climate variables, especially temperature and precipitation. Besides, the natural phenomena (e.g., drought) are considered that significantly drop the number of dengue cases by killing vector's breeding environment. However, in Kaohsiung City, Taiwan, there are evidences that the temporal pattern of dengue is correlated to drought events. Kaohsiung City experienced two main dengue outbreaks in 2002 and 2014 that both years were confirmed with serious drought. Especially in 2014, Kaohsiung City was suffered from extremely dengue outbreak in 2014 that reported the highest number of dengue cases in the history. Otherwise, another nearby city, Tainan City, had reported the biggest outbreak in 2015. This study constructs the spatiotemporal model of dengue incidences and index of drought events (Standardized Precipitation Index, SPI) based on the distributed lag nonlinear model (DLNM). Other meteorological measures are also included in the analysis.

Groundwater as an emergency source for drought mitigation in the Crocodile River catchment, South Africa

NASA Astrophysics Data System (ADS)

Mussá, F. E. F.; Zhou, Y.; Maskey, S.; Masih, I.; Uhlenbrook, S.

2015-02-01

Global climate change has received much attention worldwide in the scientific as well as in the political community, indicating that changes in precipitation, extreme droughts and floods may increasingly threaten many regions. Drought is a natural phenomenon that causes social, economical and environmental damage to society. In this study, we assess the drought intensity and severity and the groundwater potential to be used as a supplementary source of water to mitigate drought impacts in the Crocodile River catchment, a water-stressed sub-catchment of the Incomati River catchment in South Africa. The research methodology consists of three parts. First, the spatial and temporal variation of the meteorological and hydrological drought severity and intensity over the catchment were evaluated. The Standardized Precipitation Index (SPI) was used to analyse the meteorological drought and the Standardized Runoff Index (SRI) was used for the hydrological drought. Second, the water deficit in the catchment during the drought period was computed using a simple water balance method. Finally, a groundwater model was constructed in order to assess the feasibility of using groundwater as an emergency source for drought impact mitigation. Results show that the low-rainfall areas are more vulnerable to severe meteorological droughts (lower and upper crocodile). Moreover, the most water stressed sub-catchments with high level of water uses but limited storage, such as the Kaap located in the middle catchment and the Lower Crocodile sub-catchments, are more vulnerable to severe hydrological droughts. The analysis of the potential groundwater use during droughts showed that a deficit of 97 Mm3 yr-1 could be supplied from groundwater without considerable adverse impacts on the river base flow and groundwater storage. Abstraction simulations for different scenarios of extremely severe droughts reveal that it is possible to use groundwater to cope with the droughts in the catchment. However, local groundwater exploitation in Nelspruit and White River sub-catchment will cause large drawdowns (> 10 m) and high base flow reduction (> 20%). This case study shows that conjunctive water management of groundwater and surface water resources is necessary to mitigate the impacts of droughts.

Estimation of droughts indicators in the Veguita zone, Cuba

NASA Astrophysics Data System (ADS)

Cumbrera, Ramiro; Millán Vega, Humberto; Tarquis, Ana Maria; Alcolea Naranjo, Osvaldo

2016-04-01

This work has as essential objective the evaluation and analysis of the main indicators of hydrometeorology drought in Veguita, using series of daily precipitations, daily temperature and intensity of the rain. These data were contributed by the Station Agrometeorológica of Veguitas. The estimated indexes were the concentration of precipitations (CP) and the standardized index of precipitation and evapotranspiration (SPEI). The CP was calculated by means of the calculation of the index of Gini, based on the curve of Lorentz using data from 1994 until 2013. The SPEI was calculated with the software of the same name using the data from 2001 up to 2013. The main result obtained was that the precipitations in the area are concentrating, in accordance with the index of Gini and the exponential adjustment of the curve of Lorentz. Beside it, gusts dry superiors to one month were detected and the SPEI pointed out 35 months with drought, 40 humid and 81 with normal levels of rain in the last 13 years.

Comparison of SPI and SPEI indices for Drought Characterization under Climate Change Scenario in India

NASA Astrophysics Data System (ADS)

Gupta, V.; Jain, M. K.

2017-12-01

Many drought indices are available for quantifying and characterizing the drought events. Selection of a particular drought index could influence the outcome of the study. In this study, we compared two drought indices namely, Standardized precipitation index (SPI) and Standardized Precipitation-Evapotranspiration Index (SPEI) under climate change condition. Data from 7 RCM models namely, CCCma-CanESM2, CERFACS-CNRM-CM5, GFDL-ESM2M, MOHC-HadGEM2, MIROC-MIROC5, MPI-ESM-LR and MPI-ESM-MR for RCP 4.5 scenario have been used to calculate 12 month SPI and SPEI values. L-moments which provides robust distribution parameter estimation, have been used to identify best fit distribution for projected data at each grid point for each month. Mann-Kendall and Sen's slope test have been used to detect trends in drought severity, duration, peak, and interval between drought events. Results of this study reveal that SPI shows decreasing trends in drought severity, duration and peak with negative Sen's slope, however, the SPEI shows increasing trends of severity, duration and peak with a positive Sen's slope for almost all over India. The analysis reveals that projected percentage of drought affected area based on SPI in the first half of the 21st century is higher compared to those obtained using SPEI, however for the second half of the 21st century, the projected drought affected computed using SPEI is higher compared to the corresponding area obtained using SPI. Decrease in droughts severity, duration and peaks in SPI analysis could be attributed to projected increase in monsoon rainfall in Indian Subcontinent during second half of 21st century however, SPI was found incapable to account the increase in temperature thus neglecting the drying due to increased evapotranspiration whereas SPEI shows significant drying in Indian subcontinent on account of increasing trend in temperature observed in projected future RCM scenarios.

Introduction and Application of non-stationary Standardized Precipitation Index Considering Probability Distribution Function and Return Period

NASA Astrophysics Data System (ADS)

Park, J.; Lim, Y. J.; Sung, J. H.; Kang, H. S.

2017-12-01

The widely used meteorological drought index, the Standardized Precipitation Index (SPI) basically assumes stationarity, but recent change in the climate have led to a need to review this hypothesis. In this study, a new non-stationary SPI that considers not only the modified probability distribution parameter but also the return period under the non-stationary process has been proposed. The results are evaluated for two severe drought cases during the last 10 years in South Korea. As a result, SPIs considered the non-stationary hypothesis underestimated the drought severity than the stationary SPI despite these past two droughts were recognized as significantly severe droughts. It may be caused by that the variances of summer and autumn precipitation become larger over time then it can make the shape of probability distribution function wider than before. This understanding implies that drought expressions by statistical index such as SPI can be distorted by stationary assumption and cautious approach is needed when deciding drought level considering climate changes.

Introduction and application of non-stationary standardized precipitation index considering probability distribution function and return period

NASA Astrophysics Data System (ADS)

Park, Junehyeong; Sung, Jang Hyun; Lim, Yoon-Jin; Kang, Hyun-Suk

2018-05-01

The widely used meteorological drought index, the Standardized Precipitation Index (SPI), basically assumes stationarity, but recent changes in the climate have led to a need to review this hypothesis. In this study, a new non-stationary SPI that considers not only the modified probability distribution parameter but also the return period under the non-stationary process was proposed. The results were evaluated for two severe drought cases during the last 10 years in South Korea. As a result, SPIs considered that the non-stationary hypothesis underestimated the drought severity than the stationary SPI despite that these past two droughts were recognized as significantly severe droughts. It may be caused by that the variances of summer and autumn precipitation become larger over time then it can make the probability distribution wider than before. This implies that drought expressions by statistical index such as SPI can be distorted by stationary assumption and cautious approach is needed when deciding drought level considering climate changes.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Assessment of Drought Severity Using Normal Precipitation Index (Case Study: Sistan and Baluchistan Province)

NASA Astrophysics Data System (ADS)

Rahimi, D.; Movahedi, S.

2009-04-01

In the last decades, water crisis is one of the most important critical phenomenons in the environment planning and human society's management which affecting on development aspects in the international, national and regional levels. In this research, have been considered the Drought as the main parameter in water rare serious. For drought assessment, can treat the different methods, such as statistical model, meteorological and hydrological methods. In this research, have been used the Normal Precipitation index to meteorological analysis of drought severity in Sistan and Baluchistan province with high drought severity during recent years. According to the obtained result, the annual precipitation of studied area was between 36 to 52 percent more than mean precipitation of province. 10%-23 percent of precipitation amount involved the drought threshold border, 3%-13 percent of precipitations contain the weakness drought, 6.7% -23 percent were considered for moderate drought, 6%-20 percent involved the severe drought and ultimately, 6.7% to 23 percent of precipitations were considered as very severe drought. Keywords: Drought, Normal index, precipitation, Sistan and Baluchistan

Spatial drought reconstructions for central High Asia based on tree rings

NASA Astrophysics Data System (ADS)

Fang, Keyan; Davi, Nicole; Gou, Xiaohua; Chen, Fahu; Cook, Edward; Li, Jinbao; D'Arrigo, Rosanne

2010-11-01

Spatial reconstructions of drought for central High Asia based on a tree-ring network are presented. Drought patterns for central High Asia are classified into western and eastern modes of variability. Tree-ring based reconstructions of the Palmer drought severity index (PDSI) are presented for both the western central High Asia drought mode (1587-2005), and for the eastern central High Asia mode (1660-2005). Both reconstructions, generated using a principal component regression method, show an increased variability in recent decades. The wettest epoch for both reconstructions occurred from the 1940s to the 1950s. The most extreme reconstructed drought for western central High Asia was from the 1640s to the 1650s, coinciding with the collapse of the Chinese Ming Dynasty. The eastern central High Asia reconstruction has shown a distinct tendency towards drier conditions since the 1980s. Our spatial reconstructions agree well with previous reconstructions that fall within each mode, while there is no significant correlation between the two spatial reconstructions.

A nonparametric multivariate standardized drought index for characterizing socioeconomic drought: A case study in the Heihe River Basin

NASA Astrophysics Data System (ADS)

Huang, Shengzhi; Huang, Qiang; Leng, Guoyong; Liu, Saiyan

2016-11-01

Among various drought types, socioeconomic drought is the least investigated type of droughts. Most existing drought indicators ignore the role of local reservoirs and water demand in coping with climatic extremes. In this study, a Multivariate Standardized Reliability and Resilience Index (MSRRI) combining inflow-demand reliability index (IDR) and water storage resilience index (WSR) was applied to examine the evolution characteristics of the socioeconomic droughts in the Heihe River Basin, the second largest inland river basin in northwestern China. Furthermore, the cross wavelet analysis was adopted to explore the associations between annual MSRRI series and El Niño Southern Oscillation (ENSO)/Atlantic Oscillation (AO). Results indicated that: (1) the developed MSRRI is more sensitive to the onset and termination of socioeconomic droughts than IDR and WSR, owing to its joint distribution function of IDR and WSR, responding to changes in either or both of the indices; (2) the MSRRI series in the Heihe River Basin shows non-significant trends at both monthly and annual scales; (3) both ENSO and AO contribute to the changes in the socioeconomic droughts in the Heihe River Basin, and the impacts of ENSO on the socioeconomic droughts are stronger than those of AO.

Modeling drought impact occurrence based on climatological drought indices for four European countries

NASA Astrophysics Data System (ADS)

Stagge, James H.; Kohn, Irene; Tallaksen, Lena M.; Stahl, Kerstin

2014-05-01

The relationship between atmospheric conditions and the likelihood of a significant drought impact has, in the past, been difficult to quantify, particularly in Europe where political boundaries and language have made acquiring comprehensive drought impact information difficult. As such, the majority of studies linking meteorological drought with the occurrence or severity of drought impacts have previously focused on specific regions, very detailed impact types, or both. This study describes a new methodology to link the likelihood of drought impact occurrence with climatological drought indices across different European climatic regions and impact sectors using the newly developed European Drought Impact report Inventory (EDII), a collaborative database of drought impact information (www.geo.uio.no/edc/droughtdb/). The Standardized Precipitation Index (SPI) and Standardized Precipitation-Evapotranspiration Index (SPEI) are used as predictor variables to quantify meteorological drought severity over prior time periods (here 1, 2, 3, 6, 9, 12, and 24 months are used). The indices are derived using the gridded WATCH Forcing Datasets, covering the period 1958-2012. Analysis was performed using logistic regression to identify the climatological drought index and accumulation period, or linear combination of drought indices, that best predicts the likelihood of a documented drought impact, defined by monthly presence/absence. The analysis was carried out for a subset of four European countries (Germany, UK, Norway, Slovenia) and four of the best documented impact sectors: Public Water Supply, Agriculture and Livestock Farming, Energy and Industry, and Environmental Quality. Preliminary results show that drought impacts in these countries occur most frequently due to a combination of short-term (2-6 month) precipitation deficits and long-term (12-24 month) potential evapotranspiration anomaly, likely associated with increased temperatures. Agricultural drought impacts were explained best by shorter, seasonal indices (2-6 months), while impacts to the Energy sector were best explained by long-duration (12-24 month) anomalies, related to hydropower reservoir storage. Notably, drought impacts in the UK were not affected by short (< 6 month) anomalies, which may point to successful management strategies or underlying geoclimatic differences. By identifying the climatological drought indices most strongly linked to drought impact occurrence and generating regression equations that can predict the likelihood of a drought event, this research is a valuable step towards measuring and predicting drought risk. This work provides a methodological example using only a subset of European countries and impact types, but the accuracy and scope of these results will improve as the EDII grows with further contributions and collaboration.

Critical Aspects of the Coastal Drought Index: Length of Salinity Data Record and Ecological Response Data

NASA Astrophysics Data System (ADS)

Conrads, P. A.; Tufford, D. L.; Darby, L. S.

2015-12-01

The phenomenon of coastal drought has a different dynamic from upland droughts that are typically characterized by agricultural, hydrologic, meteorological, and(or) socio-economic impacts. Because of the uniqueness of drought impacts on coastal ecosystems, a coastal drought index (CDI) that uses existing salinity datasets for sites in South Carolina, Georgia, and Florida was developed using an approach similar to the Standardized Precipitation Index (SPI). CDIs characterizing the 1- to 24-month salinity conditions were developed and the evaluation of the CDI indicates that the index can be used for different estuary types (for example, brackish, olioghaline, or mesohaline), for regional comparison between estuaries, and as an index for wet conditions (high freshwater inflow) in addition to drought conditions. Unlike the SPI where long-term precipitation datasets of 50 to 100 years are available for computing the index, there are a limited number of salinity data sets of greater than 10 or 15 years for computing the CDI. To evaluate the length of salinity record necessary to compute the CDI, a 29-year dataset was resampled into 5-, 10-, 15-, and 20-year interval datasets. Comparison of the CDI for the different periods of record show that the range of salinity conditions in the 10-, 15-, and 20-year datasets were similar and results were a close approximation to the CDI computed by using the full period of record. The CDI computed with the 5-year dataset had the largest differences with the CDI computed with the 29-year dataset but did provide useful information on coastal drought and freshwater conditions. An ongoing National Integrated Drought Information System (NIDIS) drought early warning project in the Carolinas is developing ecological linkages to the CDI and evaluating the effectiveness of the CDI as a prediction tool for adaptation planning for future droughts. However, identifying potential coastal drought response datasets is a challenge. Coastal drought is a relatively new concept and existing datasets may not have been collected or understood as "drought response" datasets. We have considered drought response datasets including tree growth and liter fall, harmful algal blooms occurrence, Vibrio infection occurrence, shellfish harvesting data, and shark attacks.

Comparing the Palmer Drought Index and the Standardized Precipitation Index for Zagreb Gric Observatory

NASA Astrophysics Data System (ADS)

Pandzic, K.; Likso, T.

2012-04-01

Conventional Palmer Drought Index (PDI) and recent Standardized Precipitation Index (SPI) for Zagreb Gric Observatory are compared by spectral analysis technique. Data for a period 1862-2010 are used. The results indicate that SPI is simpler for interpretation but PDI more comprehensive index. On the other side, lack of temperature within SPI, make impossible application of it on climate change interpretation. Possible applications of them in irrigation scheduling system is considered as well for drought risk assessment.

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

NASA Astrophysics Data System (ADS)

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

2012-04-01

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

Integrated study of biomass index in La Herreria (Sierra de Guadarrama)

NASA Astrophysics Data System (ADS)

Hernandez Díaz-Ambrona, Carlos G.

2016-04-01

Drought severity has many implications for society, including its impacts on the water supply, water pollution, reservoir management and ecosystem. There have been many attempts to characterize its severity, resulting in the numerous drought indices that have been developed (Niemeyer 2008). The'biomass index', based on satellite image derived Normalized Difference Vegetation Index (NDVI) has been used in several countries for pasture and forage crops for some years (Rao, 2010; Escribano-Rodriguez et al., 2014). NDVI generally provides a broad overview of the vegetation condition and spatial vegetation distribution in a region. Vegetative drought is closely related with weather impacts. However, in NDVI, the weather component gets subdued by the strong ecological component. Another vegetation index is Vegetation Condition Index (VCI) that separates the short-term weather-related NDVI fluctuations from the long-term ecosystem changes (Kogan, 1990). Therefore, while NDVI shows seasonal vegetation dynamics, VCI rescales vegetation dynamics between 0 and 100 to reflect relative changes in the vegetation condition from extremely bad to optimal (Kogan et al., 2003). In this work a pasture area at La Herreria (Sierra de Guadarrama, Spain) has been delimited. Then, NDVI historical data are reconstructed based on remote sensing imaging MODIS, with 500x500m2 resolution. From the closest meteorological station (Santolaria-Canales, 2015) records of weekly precipitation, temperature and evapotranspiration from 2001 till 2012 were obtained. Standard Precipitation Index (SPI), Crop Moisture Index (CMI) (Palmer, 1968) and Evapotranspiration-Precipitation Ratio (EPR) are calculated in an attempt to relate them to several vegetation indexes: NDVI, VCI and NDVI Change Ratio to Median (RMNDVI). The results are discussed in the context of pasture index insurance. References Escribano Rodriguez, J.Agustín, Carlos Gregorio Hernández Díaz-Ambrona and Ana María Tarquis Alfonso. Selection of vegetation indices to estimate pasture production in Dehesas. PASTOS, 44(2), 6-18, 2014. Kogan, F. N., 1990. Remote sensing of weather impacts on vegetation in non-homogeneous areas. Int. J. Remote Sensing, 11(8), pp. 1405-1419. Kogan, F. N., Gitelson, A., Edige, Z., Spivak, l., and Lebed, L., 2003. AVHRR-Based Spectral Vegetation Index for Quantitative Assessment of Vegetation State and Productivity: Calibration and Validation. Photogrammetric Engineering & Remote Sensing, 69(8), pp. 899-906. Niemeyer, S., 2008. New drought indices. First Int. Conf. on Drought Management: Scientific and Technological Innovations, Zaragoza, Spain, Joint Research Centre of the European Commission. Palmer, W.C., 1968. Keeping track of crop moisture conditions, nationwide: The new Crop Moisture Index. Weatherwise 21, 156-161. Rao, K.N. 2010. Index based Crop Insurance. Agriculture and Agricultural Science Procedia 1, 193-203. Santolaria-Canales, Edmundo and the GuMNet Consortium Team (2015). GuMNet - Guadarrama Monitoring Network. Installation and set up of a high altitude monitoring network, north of Madrid. Spain. Geophysical Research Abstracts, 17, EGU2015-13989-2 Web: http://www.ucm.es/gumnet/

Spatiotemporal Drought Analysis and Drought Indices Comparison in India

NASA Astrophysics Data System (ADS)

Janardhanan, A.

2017-12-01

Droughts and floods are an ever-occurring phenomenon that has been wreaking havoc on humans since the start of time. As droughts are on a very large scale, studying them within a regional context can minimize confounding factors such as climate change. Droughts and floods are extremely erratic and very difficult to predict and therefore necessitate modeling through advanced statistics. The SPI (Standard Precipitation Index) and the SPEI (Standard Precipitation Evapotranspiration Index) are two ways to temporally model drought and flood patterns across each metrological sub basin in India over a variety of different time scales. SPI only accounts for precipitation values, while the SPEI accounts for both precipitation and temperature and is commonly regarded as a more reliable drought index. Using monthly rainfall and temperature data from 1871-2016, these two indices were calculated. The results depict the drought and flood severity index, length of drought, and average SPI or SPEI value for each meteorological sub region in India. A Wilcox Ranksum test was then conducted to determine whether these two indices differed over the long term for drought analysis. The drought return periods were analyzed to determine if the population mean differed between the SPI and SPEI values. Our analysis found no statistical difference between SPI and SPEI with regards to long-term drought analysis. This indicates that temperature is not needed when modeling drought on a long-term time scale and that SPI is just as effective as SPEI, which has the potential to save a lot of time and resources on calculating drought indices.

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

USGS Publications Warehouse

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

2015-01-01

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

Soil- and crop-dependent variation in correlation lag between precipitation and agricultural drought indices as predicted by the SWAP model

NASA Astrophysics Data System (ADS)

Wright, Azin; Cloke, Hannah; Verhoef, Anne

2017-04-01

Droughts have a devastating impact on agriculture and economy. The risk of more frequent and more severe droughts is increasing due to global warming and certain anthropogenic activities. At the same time, the global population continues to rise and the need for sustainable food production is becoming more and more pressing. In light of this, drought prediction can be of great value; in the context of early warning, preparedness and mitigation of drought impacts. Prediction of meteorological drought is associated with uncertainties around precipitation variability. As meteorological drought propagates, it can transform into agricultural drought. Determination of the maximum correlation lag between precipitation and agricultural drought indices can be useful for prediction of agricultural drought. However, the influence of soil and crop type on the lag needs to be considered, which we explored using a 1-D Soil-Vegetation-Atmosphere-Transfer model (SWAP (http://www.swap.alterra.nl/), with the following configurations, all forced with ERA-Interim weather data (1979 to 2014): i) different crop types in the UK; ii) three generic soil types (clay, loam and sand) were considered. A Sobol sensitivity analysis was carried out (perturbing the SWAP model van Genuchten soil hydraulic parameters) to study the effect of soil type uncertainty on the water balance variables. Based on the sensitivity analysis results, a few variations of each soil type were selected. Agricultural drought indices including Soil Moisture Deficit Index (SMDI) and Evapotranspiration Deficit Index (ETDI) were calculated. The maximum correlation lag between precipitation and these drought indices was calculated, and analysed in the context of crop and soil model parameters. The findings of this research can be useful to UK farming, by guiding government bodies such as the Environment Agency when issuing drought warnings and implementing drought measures.

A hybrid spatiotemporal drought forecasting model for operational use

NASA Astrophysics Data System (ADS)

Vasiliades, L.; Loukas, A.

2010-09-01

Drought forecasting plays an important role in the planning and management of natural resources and water resource systems in a river basin. Early and timelines forecasting of a drought event can help to take proactive measures and set out drought mitigation strategies to alleviate the impacts of drought. Spatiotemporal data mining is the extraction of unknown and implicit knowledge, structures, spatiotemporal relationships, or patterns not explicitly stored in spatiotemporal databases. As one of data mining techniques, forecasting is widely used to predict the unknown future based upon the patterns hidden in the current and past data. This study develops a hybrid spatiotemporal scheme for integrated spatial and temporal forecasting. Temporal forecasting is achieved using feed-forward neural networks and the temporal forecasts are extended to the spatial dimension using a spatial recurrent neural network model. The methodology is demonstrated for an operational meteorological drought index the Standardized Precipitation Index (SPI) calculated at multiple timescales. 48 precipitation stations and 18 independent precipitation stations, located at Pinios river basin in Thessaly region, Greece, were used for the development and spatiotemporal validation of the hybrid spatiotemporal scheme. Several quantitative temporal and spatial statistical indices were considered for the performance evaluation of the models. Furthermore, qualitative statistical criteria based on contingency tables between observed and forecasted drought episodes were calculated. The results show that the lead time of forecasting for operational use depends on the SPI timescale. The hybrid spatiotemporal drought forecasting model could be operationally used for forecasting up to three months ahead for SPI short timescales (e.g. 3-6 months) up to six months ahead for large SPI timescales (e.g. 24 months). The above findings could be useful in developing a drought preparedness plan in the region.

European drought climatologies for the period 1950 to 2012

NASA Astrophysics Data System (ADS)

Spinoni, Jonathan; Naumann, Gustavo; Vogt, Jürgen V.; Barbosa, Paulo

2014-05-01

In the context of global climate change, characterized in particular by rising temperatures and more extreme weather events, drought is one of the most relevant natural disasters that has hit Europe frequently in the last decades. This paper presents climatologies of a set of drought indicators and derived drought characteristics at European scale for the period 1950-2012. Following the definitions in Spinoni et al. (2013), we computed drought frequency, duration, severity, and maximum intensity on a grid with spatial resolution of 0.25°x0.25°. Calculations have been based on three well-known drought indicators calculated for time scales of 3 and 12 months: the Standardized Precipitation Index (SPI), the Standardized Precipitation-Evapotranspiration Index (SPEI), and the Reconnaissance Drought Index (RDI). Indicators have been calculated on a monthly basis for the period 1951-2012, using statistical distributions fitted to a 30-year baseline period (1971-2000). Input data stem from the E-OBS (version 9.0) European grids (0.25°x0.25°) provided by the Royal Meteorological Service of The Netherlands (KNMI). Monthly precipitation data served as input for all indicators, while mean monthly temperature data were used to calculate Thornthwaite's potential evapotranspiration necessary to calculate SPEI and RDI. On the basis of these indicators, we then quantified, on a monthly basis, the total European area under meteorological drought conditions from 1950 to 2012 and their intensity. We further sub-divided Europe into 14 regions according to geographical borders and climatic features and for each of them we computed linear trends of different drought characteristics (i.e. frequency, duration, severity, and intensity) for the entire period, and for the sub-periods 1951-1980 and 1981-2010. Results show that the Mediterranean, the Balkans, and Eastern Europe are characterized by increasing drought frequency, duration, severity, and maximum intensity, while Russia and Northern Europe are characterized by a decrease, in particular with respect to drought severity. Finally, the most relevant drought events per region are presented. Spinoni J., Naumann G., Carrao, H., Barbosa P., and Vogt J.V. (2013): World drought frequency, duration, and severity for 1951-2010. Int. J. Climatol., DOI: 10.1002/joc.3875.

Drought impacts on vegetation activity in the Mediterranean region: An assessment using remote sensing data and multi-scale drought indicators

NASA Astrophysics Data System (ADS)

Gouveia, C. M.; Trigo, R. M.; Beguería, S.; Vicente-Serrano, S. M.

2017-04-01

The present work analyzes the drought impacts on vegetation over the entire Mediterranean basin, with the purpose of determining the vegetation communities, regions and seasons at which vegetation is driven by drought. Our approach is based on the use of remote sensing data and a multi-scalar drought index. Correlation maps between fields of monthly Normalized Difference Vegetation Index (NDVI) and the Standardized Precipitation-Evapotranspiration Index (SPEI) at different time scales (1-24 months) were computed for representative months of winter (Feb), spring (May), summer (Aug) and fall (Nov). Results for the period from 1982 to 2006 show large areas highly controlled by drought, although presenting high spatial and seasonal differences, with a maximum influence in August and a minimum in February. The highest correlation values are observed in February for 3 months' time scale and in May for 6 and 12 months. The higher control of drought on vegetation in February and May is obtained mainly over the drier vegetation communities (Mediterranean Dry and Desertic) at shorter time scales (3 to 9 months). Additionally, in February the impact of drought on vegetation is lower for Temperate Oceanic and Continental vegetation types and takes place at longer time scales (18-24). The dependence of drought time-scale response with water balance, as obtained through a simple difference between precipitation and reference evapotranspiration, varies with vegetation communities. During February and November low water balance values correspond to shorter time scales over dry vegetation communities, whereas high water balance values implies longer time scales over Temperate Oceanic and Continental areas. The strong control of drought on vegetation observed for Mediterranean Dry and Desertic vegetation types located over areas with high negative values of water balance emphasizes the need for an early warning drought system covering the entire Mediterranean basin. We are confident that these results will provide a useful tool for drought management plans and play a relevant role in mitigating the impact of drought episodes.

Developing the vegetation drought response index for South Korea (VegDRI-SKorea) to assess the vegetation condition during drought events

USDA-ARS?s Scientific Manuscript database

Drought poses significant water and food security concerns in many parts of the world and can lead to negative agricultural, economic, and environmental impacts. The Vegetation Drought Response Index (VegDRI) approach has the flexibility to be adapted for other regions of the world using the climate...

A five-year analysis of MODIS NDVI and NDWI for grassland drought assessment over the central Great Plains of the United States

USGS Publications Warehouse

Gu, Yingxin; Brown, Jesslyn F.; Verdin, J.P.; Wardlow, B.

2007-01-01

A five-year (2001–2005) history of moderate resolution imaging spectroradiometer (MODIS) normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) data was analyzed for grassland drought assessment within the central United States, specifically for the Flint Hills of Kansas and Oklahoma. Initial results show strong relationships among NDVI, NDWI, and drought conditions. During the summer over the Tallgrass Prairie National Preserve, the average NDVI and NDWI were consistently lower (NDVI < 0.5 and NDWI < 0.3) under drought conditions than under non-drought conditions (NDVI>0.6 and NDWI>0.4). NDWI values exhibited a quicker response to drought conditions than NDVI. Analysis revealed that combining information from visible, near infrared, and short wave infrared channels improved sensitivity to drought severity. The proposed normalized difference drought index (NDDI) had a stronger response to summer drought conditions than a simple difference between NDVI and NDWI, and is therefore a more sensitive indicator of drought in grasslands than NDVI alone.

Assessing changes in drought characteristics with standardized indices

NASA Astrophysics Data System (ADS)

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

2010-05-01

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

Drought assessment by evapotranspiration mapping in Twente

NASA Astrophysics Data System (ADS)

Eden, U.; Timmermans, J.; van der Velde, R.; Su, Z.

2012-04-01

Drought is a reoccurring worldwide problem with impacts ranging from food production to infrastructure. Droughts are different from other natural hazards (floods, hurricanes, and earthquakes) because the effects can only be witnessed slowly and with a time delay. Effects of droughts are diverse, like famine and migration of people. Droughts are caused by natural causes but also by interaction between the natural events and water demand. Not only typical dry regions, like the Horn of Africa, are affected, but even semi-humid environments, like Europe. Temperature rise and precipitation deficit in the summers of 2003 and 2006 caused substantial crop losses in the agricultural sector in the Netherlands. In addition increased river water temperatures and low water levels caused cooling problems for power plants. Heat waves and prolonged absence of precipitation is expected to increase due to climate change. Therefore assessing and monitoring drought in the Netherlands is thus very important. Various drought indices are available to assess the severity, duration and spatial extend of the drought. Some of the commonly indices used are Standardized precipitation index (SPI) and the Palmer Drought Severity Index (PDSI). However each of these indices do not take into account the actual state of the land surface in respect to the dryness. By analysing drought through actual evapotranspiration (ET) estimations from remote sensing this can be circumvented. The severity of the droughts was quantified by ET-mapping from 2003-2010. The assessment was based on the spatial and temporal distribution of ET using the Evapotranspiration Deficit Index (ETDI) drought index. Surface energy fluxes, like ET, were estimated using WACMOS methodology. The input data consisted of remote sensing products like land surface temperature, LAI, and albedo from MODIS; and meteorological data like air-temperature, humidity and wind speed from the European Centre for Medium weather forecast (ECMWF). ETDI was then calculated using the estimated actual ET in combination with reference ET from Penman-Moneith. Investigations on temperature and precipitation anomalies, using SPI, are also included because of their contribution to the droughts. For this precipitation data from ground measurements were used to calculate the SPI for comparison with ETDI. Preliminary results show that SEBS ET from MODIS 1km resolution and ECMWF can be used for estimating ET for Twente region. The ET maps show that evapotranspiration in all years follow a seasonal trend with higher ET during the growing season as compared to other seasons. Investigation into ET shows small spatial variability, and investigation into SPI shows large temporal variability with 2003 and 2006 being very dry years.

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

USGS Publications Warehouse

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

2016-01-01

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

Analysis of trends and dominant periodicities in drought variables in India: A wavelet transform based approach

NASA Astrophysics Data System (ADS)

Joshi, Nitin; Gupta, Divya; Suryavanshi, Shakti; Adamowski, Jan; Madramootoo, Chandra A.

2016-12-01

In this study, seasonal trends as well as dominant and significant periods of variability of drought variables were analyzed for 30 rainfall subdivisions in India over 141 years (1871-2012). Standardized precipitation index (SPI) was used as a meteorological drought indicator, and various drought variables (monsoon SPI, non-monsoon SPI, yearly SPI, annual drought duration, annual drought severity and annual drought peak) were analyzed. Discrete wavelet transform was used in conjunction with the Mann-Kendall test to analyze trends and dominant periodicities associated with the drought variables. Furthermore, continuous wavelet transform (CWT) based global wavelet spectrum was used to analyze significant periods of variability associated with the drought variables. From the trend analysis, we observed that over the second half of the 20th century, drought occurrences increased significantly in subdivisions of Northeast and Central India. In both short-term (2-8 years) and decadal (16-32 years) periodicities, the drought variables were found to influence the trend. However, CWT analysis indicated that the dominant periodic components were not significant for most of the geographical subdivisions. Although inter-annual and inter-decadal periodic components play an important role, they may not completely explain the variability associated with the drought variables across the country.

Contribution of precipitation and reference evapotranspiration to drought indices under different climates

NASA Astrophysics Data System (ADS)

Vicente-Serrano, Sergio M.; Van der Schrier, Gerard; Beguería, Santiago; Azorin-Molina, Cesar; Lopez-Moreno, Juan-I.

2015-07-01

In this study we analyzed the sensitivity of four drought indices to precipitation (P) and reference evapotranspiration (ETo) inputs. The four drought indices are the Palmer Drought Severity Index (PDSI), the Reconnaissance Drought Index (RDI), the Standardized Precipitation Evapotranspiration Index (SPEI) and the Standardized Palmer Drought Index (SPDI). The analysis uses long-term simulated series with varying averages and variances, as well as global observational data to assess the sensitivity to real climatic conditions in different regions of the World. The results show differences in the sensitivity to ETo and P among the four drought indices. The PDSI shows the lowest sensitivity to variation in their climate inputs, probably as a consequence of the standardization procedure of soil water budget anomalies. The RDI is only sensitive to the variance but not to the average of P and ETo. The SPEI shows the largest sensitivity to ETo variation, with clear geographic patterns mainly controlled by aridity. The low sensitivity of the PDSI to ETo makes the PDSI perhaps less apt as the suitable drought index in applications in which the changes in ETo are most relevant. On the contrary, the SPEI shows equal sensitivity to P and ETo. It works as a perfect supply and demand system modulated by the average and standard deviation of each series and combines the sensitivity of the series to changes in magnitude and variance. Our results are a robust assessment of the sensitivity of drought indices to P and ETo variation, and provide advice on the use of drought indices to detect climate change impacts on drought severity under a wide variety of climatic conditions.

Evolution and characterization of drought events from GRACE and other satellite and observation.

NASA Astrophysics Data System (ADS)

Zhao, M.; A, G.; Velicogna, I.; Kimball, J. S.

2015-12-01

We use GRACE Terrestrial Water Storage (TWS) changes to calculate a newly developed global drought severity index (GRACE-DSI) for monthly monitoring of water supply changes during 2002-2015. We compare GRACE-DSI with Palmer Drought Severity Index (PDSI) and other ancillary data to characterize drought timing, evolution and magnitude in the continental US since 2002. Overall GRACE-DSI and PDSI show an excellent correspondence in the US. However PDSI is very sensitive to atmospheric moisture stress, while GRACE-DSI only responds to changes in terrestrial water storage. We use the complementary nature of these two indices together with temperature and precipitation observations to characterize drought evolution and its nature. For instance, during the 2012 flash drought in the Great Plains, the PDSI decreases several months earlier than the GRACE-DSI in response to the enhanced atmosphere moisture demand caused by unusual early season warming. When the drought peaks later in the summer, the PDSI indicates exceptional drought, while the GRACE-DSI observes moderate drought conditions in the underlying total water supply, implying a meteorological drought in nature. GRACE-DSI is based solely on satellite observations; hence it has the advantage of not being affected by uncertainty associated with variable that are not well known at the global scale (e.g. precipitation estimates) and by biases associated to global climate model outputs. We find that GRACE-DSI captures major drought events in the globe occurring during 2002-2015, including those in sub-Sahara Africa, Australia, Amazon, Asia, North America and the Arctic.

Historical and future drought in Bangladesh using copula-based bivariate regional frequency analysis

NASA Astrophysics Data System (ADS)

Mortuza, Md Rubayet; Moges, Edom; Demissie, Yonas; Li, Hong-Yi

2018-02-01

The study aims at regional and probabilistic evaluation of bivariate drought characteristics to assess both the past and future drought duration and severity in Bangladesh. The procedures involve applying (1) standardized precipitation index to identify drought duration and severity, (2) regional frequency analysis to determine the appropriate marginal distributions for both duration and severity, (3) copula model to estimate the joint probability distribution of drought duration and severity, and (4) precipitation projections from multiple climate models to assess future drought trends. Since drought duration and severity in Bangladesh are often strongly correlated and do not follow same marginal distributions, the joint and conditional return periods of droughts are characterized using the copula-based joint distribution. The country is divided into three homogeneous regions using Fuzzy clustering and multivariate discordancy and homogeneity measures. For given severity and duration values, the joint return periods for a drought to exceed both values are on average 45% larger, while to exceed either value are 40% less than the return periods from the univariate frequency analysis, which treats drought duration and severity independently. These suggest that compared to the bivariate drought frequency analysis, the standard univariate frequency analysis under/overestimate the frequency and severity of droughts depending on how their duration and severity are related. Overall, more frequent and severe droughts are observed in the west side of the country. Future drought trend based on four climate models and two scenarios showed the possibility of less frequent drought in the future (2020-2100) than in the past (1961-2010).

Impacts of Water Stress on Forest Recovery and Its Interaction with Canopy Height.

PubMed

Xu, Peipei; Zhou, Tao; Yi, Chuixiang; Luo, Hui; Zhao, Xiang; Fang, Wei; Gao, Shan; Liu, Xia

2018-06-13

Global climate change is leading to an increase in the frequency, intensity, and duration of drought events, which can affect the functioning of forest ecosystems. Because human activities such as afforestation and forest attributes such as canopy height may exhibit considerable spatial differences, such differences may alter the recovery paths of drought-impacted forests. To accurately assess how climate affects forest recovery, a quantitative evaluation on the effects of forest attributes and their possible interaction with the intensity of water stress is required. Here, forest recovery following extreme drought events was analyzed for Yunnan Province, southwest China. The variation in the recovery of forests with different water availability and canopy heights was quantitatively assessed at the regional scale by using canopy height data based on light detection and ranging (LiDAR) measurements, enhanced vegetation index data, and standardized precipitation evapotranspiration index (SPEI) data. Our results indicated that forest recovery was affected by water availability and canopy height. Based on the enhanced vegetation index measures, shorter trees were more likely to recover than taller ones after drought. Further analyses demonstrated that the effect of canopy height on recovery rates after drought also depends on water availability—the effect of canopy height on recovery diminished as water availability increased after drought. Additional analyses revealed that when the water availability exceeded a threshold (SPEI > 0.85), no significant difference in the recovery was found between short and tall trees ( p > 0.05). In the context of global climate change, future climate scenarios of RCP2.6 and RCP8.5 showed more frequent water stress in Yunnan by the end of the 21st century. In summary, our results indicated that canopy height casts an important influence on forest recovery and tall trees have greater vulnerability and risk to dieback and mortality from drought. These results may have broad implications for policies and practices of forest management.

An ensemble-ANFIS based uncertainty assessment model for forecasting multi-scalar standardized precipitation index

NASA Astrophysics Data System (ADS)

Ali, Mumtaz; Deo, Ravinesh C.; Downs, Nathan J.; Maraseni, Tek

2018-07-01

Forecasting drought by means of the World Meteorological Organization-approved Standardized Precipitation Index (SPI) is considered to be a fundamental task to support socio-economic initiatives and effectively mitigating the climate-risk. This study aims to develop a robust drought modelling strategy to forecast multi-scalar SPI in drought-rich regions of Pakistan where statistically significant lagged combinations of antecedent SPI are used to forecast future SPI. With ensemble-Adaptive Neuro Fuzzy Inference System ('ensemble-ANFIS') executed via a 10-fold cross-validation procedure, a model is constructed by randomly partitioned input-target data. Resulting in 10-member ensemble-ANFIS outputs, judged by mean square error and correlation coefficient in the training period, the optimal forecasts are attained by the averaged simulations, and the model is benchmarked with M5 Model Tree and Minimax Probability Machine Regression (MPMR). The results show the proposed ensemble-ANFIS model's preciseness was notably better (in terms of the root mean square and mean absolute error including the Willmott's, Nash-Sutcliffe and Legates McCabe's index) for the 6- and 12- month compared to the 3-month forecasts as verified by the largest error proportions that registered in smallest error band. Applying 10-member simulations, ensemble-ANFIS model was validated for its ability to forecast severity (S), duration (D) and intensity (I) of drought (including the error bound). This enabled uncertainty between multi-models to be rationalized more efficiently, leading to a reduction in forecast error caused by stochasticity in drought behaviours. Through cross-validations at diverse sites, a geographic signature in modelled uncertainties was also calculated. Considering the superiority of ensemble-ANFIS approach and its ability to generate uncertainty-based information, the study advocates the versatility of a multi-model approach for drought-risk forecasting and its prime importance for estimating drought properties over confidence intervals to generate better information for strategic decision-making.

An Evaluation of Drought Indices in Different Climatic Regions

NASA Astrophysics Data System (ADS)

Shahabfar, A.; Eitzinger, J.

2009-04-01

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

Drought Risk Identification: Early Warning System of Seasonal Agrometeorological Drought

NASA Astrophysics Data System (ADS)

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

2014-05-01

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

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

NASA Astrophysics Data System (ADS)

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

2015-11-01

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

Severe Drought Event in Indonesia Following 2015/16 El Niño/positive Indian Dipole Events

NASA Astrophysics Data System (ADS)

Lestari, D. O.; Sutriyono, E.; Sabaruddin; Iskandar, I.

2018-04-01

During boreal fall and winter 2015/16, Indonesia experienced catastrophic drought event causing many environmental problems. This study explored dynamical evolution of drought event in Indonesia associated with those two climate modes. Based on the Niño3.4 index, the evolution of the El Niño has started in April 2015, reached its peak in January 2016 and terminated in April 2016. Meanwhile, the Dipole Mode Index (DMI) revealed that the evolution of positive Indian Ocean Dipole has started in August, reached its peak in September and terminated in November 2015. It is shown that during those two events, Indonesia experienced severe drought in which the precipitation was extremely decreased. During the peak drought condition co-occurring with the dry season, the anomalous of precipitation reached ‑450 mm/month in September 2015. The peak of the drought was associated with the El Niño and positive Indian Ocean Dipole sea surface temperature anomaly (SSTA) patterns, in which negative SSTA covered the eastern tropical Indian Ocean and the western Pacific Ocean including Indonesia seas. Meanwhile, positive SSTA observed in the western tropical Indian Ocean and Eastern Pacific Ocean.

Groundwater as an emergency source for drought mitigation in the Crocodile River catchment, South Africa

NASA Astrophysics Data System (ADS)

Mussá, F. E. F.; Zhou, Y.; Maskey, S.; Masih, I.; Uhlenbrook, S.

2014-03-01

Global climate change has received much attention worldwide in the scientific as well as in the political community, indicating that changes in precipitation, extreme droughts and floods may threaten increasingly many regions. Drought is a natural phenomenon that may cause social, economical and environmental damages to the society. In this study, we assess the drought intensity and severity and the groundwater potential to be used as a supplement source of water to mitigate drought impacts in the Crocodile River catchment, a water-stressed sub-catchment of the Incomati River catchment in South Africa. The research methodology consists mainly of three parts. First, the spatial and temporal variation of the meteorological and hydrological drought severity and intensity over the catchment were evaluated. The Standardized Precipitation Index (SPI) was used to analyse the meteorological drought and the Standardized Runoff Index (SRI) was used for the hydrological drought. Second, the water deficit in the catchment during the drought period was computed using a simple water balance method. Finally, a groundwater model was constructed in order to assess the feasibility of using groundwater as an emergency source for drought impact mitigation. Results show that the meteorological drought severity varies accordingly with the precipitation; the low rainfall areas are more vulnerable to severe meteorological droughts (lower and upper crocodile). Moreover, the most water stressed sub-catchments with high level of water uses but limited storage, such as the Kaap located in the middle catchment and the Lower Crocodile sub-catchments are those which are more vulnerable to severe hydrological droughts. The analysis of the potential groundwater use during droughts showed that a deficit of 97 Mm3 yr-1 could be supplied from groundwater without considerable adverse impacts on the river base flow and groundwater storage. Abstraction simulations for different scenarios of extremely severe droughts reveal that it is possible to use groundwater to cope with the droughts in the catchment. However, local groundwater exploitation in Nelspruit and White River sub-catchment will cause large drawdowns (> 10 m) and high base flow reduction (> 20%). This case study shows that conjunctive water management of groundwater and surface water resources is the necessary to mitigate the impacts of droughts.

Drought Characteristics Based on the Retrieved Paleoprecipitation in Indus and Ganges River Basins

NASA Astrophysics Data System (ADS)

Davtalabsabet, R.; Wang, D.; Zhu, T.; Ringler, C.

2014-12-01

Indus and Ganges River basins (IGRB), which cover the major parts of India, Nepal, Bangladesh and Pakistan, are considered as the most important socio-economic regions in South Asia. IGRB support the food security of hundreds of millions people in South Asia. The food production in IGRB strictly relies on the magnitude and spatiotemporal pattern of monsoon precipitation. Due to severe drought during the last decades and food production failure in IGRB, several studies have focused on understanding the main drivers for south Asia monsoon failures and drought characteristics based on the historical data. However, the period of available historical data is not enough to address the full characteristic of drought under a changing climate. In this study, an inverse Palmer Drought Severity Index (PDSI) model is developed to retrieve the paleoprecipitation back to 700 years in the region, taking the inputs of available soil water capacity, temperature, and previous reconstructed PDSI based on tree-ring analysis at 2.5 degree resolution. Based on the retrieved paleoprecipitation, drought frequency and intensity are quantified for two periods of 1300-1899 (the reconstruction period) and 1900-2010 (the instrumental period). Previous studies have shown that in IGRB, a severe drought occurs when the annual precipitation deficit, compared with the long-term average precipitation, is greater than 10%. Climatic drought frequency is calculated as the percentage of years with predefined severe droughts. Drought intensity is defined as the average precipitation deficit during all of the years identified as severe droughts. Results show that the drought frequency, as well as the spatial extent, has significantly increased from the reconstruction period to the instrumental period. The drought frequency in the Indus River basin is higher than that in the Ganges River basin. Several mega-droughts are identified during the reconstruction period.

The European 2015 drought from a groundwater perspective

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Multi-Scale Drought Analysis using Thermal Remote Sensing: A Case Study in Georgia’s Altamaha River Watershed

NASA Astrophysics Data System (ADS)

Jacobs, J. M.; Bhat, S.; Choi, M.; Mecikalski, J. R.; Anderson, M. C.

2009-12-01

The unprecedented recent droughts in the Southeast US caused reservoir levels to drop dangerously low, elevated wildfire hazard risks, reduced hydropower generation and caused severe economic hardships. Most drought indices are based on recent rainfall or changes in vegetation condition. However in heterogeneous landscapes, soils and vegetation (type and cover) combine to differentially stress regions even under similar weather conditions. This is particularly true for the heterogeneous landscapes and highly variable rainfall in the Southeastern United States. This research examines the spatiotemperal evolution of watershed scale drought using a remotely sensed stress index. Using thermal-infrared imagery, a fully automated inverse model of Atmosphere-Land Exchange (ALEXI), GIS datasets and analysis tools, modeled daily surface moisture stress is examined at a 10-km resolution grid covering central to southern Georgia. Regional results are presented for the 2000-2008 period. The ALEXI evaporative stress index (ESI) is compared to existing regional drought products and validated using local hydrologic measurements in Georgia’s Altamaha River watershed at scales from 10 to 10,000 km2.

The impact of climate change on the drought variability over Australia

NASA Astrophysics Data System (ADS)

Kirono, D. G. C.; Hennessy, K.; Mpelasoka, F.; Bathols, J.; Kent, D.

2009-04-01

Drought has significant environmental and socio-economic impacts in Australia. Government assistance for drought events is guided by the current National Drought Policy (NDP). The Commonwealth Government provides support to farmers and rural communities under the Exceptional Circumstances (EC) arrangements and other drought programs, while state and territory governments also participate in the NDP and provide support measures of their own. To be classified as an EC event, the event must be rare, that is must not have occurred more than once on average in every 20-25 years. Given the likely increase in the area of the world affected by droughts in future due to climate change (IPCC, 2007), this paper presents assessments on how climate change may affect the concept of a one in 20-25 year event into the future for Australia. As droughts can be experienced and defined in different ways, many drought indices are available to monitor and to assess drought conditions. Commonly, these indices are categorised into four types: meteorological, hydrological, agricultural, and socio-economic. The meteorological drought indices are more widely used because they require data that are readily available and that they are relatively easy to calculate. However, meteorological drought indices based on rainfall alone fail to include the important contribution of evaporation. Here, the assessment is made using outputs of 13 global climate models (GCMs) and a meteorological drought index called the Reconnaissance Drought Index (RDI). It incorporates the aggregated deficits between the rainfall and the evaporative demand of the atmosphere. If the RDI were the sole trigger for EC declarations, then the mean projections indicate that more declarations would be likely in the future. As a comparison, results from an assessment based on other measures (temperature, rainfall, and soil wetness) will also be presented. IPCC, 2007: Climate Change 2007 - The physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (eds. Solomon, S. et al.). Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, www.ipcc.ch

DroughtView: Satellite Based Drought Monitoring and Assessment

NASA Astrophysics Data System (ADS)

Hartfield, K. A.; Van Leeuwen, W. J. D.; Crimmins, M.; Marsh, S. E.; Torrey, Y.; Rahr, M.; Orr, B. J.

2014-12-01

Drought is an ever growing concern within the United States and Mexico. Extended periods of below-average precipitation can adversely affect agricultural production and ecosystems, impact local water resources and create conditions prime for wildfire. DroughtView (www.droughtview.arizona.edu) is a new on-line resource for scientists, natural resource managers, and the public that brings a new perspective to remote-sensing based drought impact assessment that is not currently available. DroughtView allows users to monitor the impact of drought on vegetation cover for the entire continental United States and the northern regions of Mexico. As a spatially and temporally dynamic geospatial decision support tool, DroughtView is an excellent educational introduction to the relationship between remotely sensed vegetation condition and drought. The system serves up Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) data generated from 250 meter 16-day composite Moderate-resolution Imaging Spectroradiometer (MODIS) imagery from 2000 to the present. Calculation of difference from average, previous period and previous year greenness products provide the user with a proxy for drought conditions and insight on the secondary impacts of drought, such as wildfire. The various image products and overlays are served up via the ArcGIS Server platform. DroughtView serves as a useful tool to introduce and teach vegetation time series analysis to those unfamiliar with the science. High spatial resolution imagery is available as a reference layer to locate points of interest, zoom in and export images for implementation in reports and presentations. Animation of vegetation time series allows users to examine ecosystem disturbances and climate data is also available to examine the relationship between precipitation, temperature and vegetation. The tool is mobile friendly allowing users to access the system while in the field. The systems capabilities and applications will be demonstrated live during the poster session. Expansion of DroughtView includes future plans to add snow products, phenology data and climate scenarios. Extension of the spatial coverage of the data to other parts of the world is also planned.

[Characteristics and adaptation of seasonal drought in southern China under the background of climate change. V. Seasonal drought characteristics division and assessment in southern China].

PubMed

Huang, Wan-Hua; Sui, Yue; Yang, Xiao-Guang; Dai, Shu-Wei; Li, Mao-Song

2013-10-01

Zoning seasonal drought based on the study of drought characteristics can provide theoretical basis for formulating drought mitigation plans and improving disaster reduction technologies in different arid zones under global climate change. Based on the National standard of meteorological drought indices and agricultural drought indices and the 1959-2008 meteorological data from 268 meteorological stations in southern China, this paper analyzed the climatic background and distribution characteristics of seasonal drought in southern China, and made a three-level division of seasonal drought in this region by the methods of combining comprehensive factors and main factors, stepwise screening indices, comprehensive disaster analysis, and clustering analysis. The first-level division was with the annual aridity index and seasonal aridity index as the main indices and with the precipitation during entire year and main crop growing season as the auxiliary indices, dividing the southern China into four primary zones, including semi-arid zone, sub-humid zone, humid zone, and super-humid zone. On this basis, the four primary zones were subdivided into nine second-level zones, including one semi-arid area-temperate-cold semi-arid hilly area in Sichuan-Yunnan Plateau, three sub-humid areas of warm sub-humid area in the north of the Yangtze River, warm-tropical sub-humid area in South China, and temperate-cold sub-humid plateau area in Southwest China, three humid areas of temperate-tropical humid area in the Yangtze River Basin, warm-tropical humid area in South China, and warm humid hilly area in Southwest China, and two super-humid areas of warm-tropical super-humid area in South China and temperate-cold super-humid hilly area in the south of the Yangtze River and Southwest China. According to the frequency and intensity of multiple drought indices, the second-level zones were further divided into 29 third-level zones. The distribution of each seasonal drought zone was illustrated, and the zonal drought characteristics and their impacts on the agricultural production were assessed. Accordingly, the drought prevention measures were proposed.

Development of Water Resources Drought Early Warning System

NASA Astrophysics Data System (ADS)

Chen, B. P. T.; Chen, C. H.

2017-12-01

Signs of impending drought are often vague and result from hydrologic uncertainty. Because of this, determining the appropriate time to enforce water supply restrictions is difficult. This study proposes a drought early warning index (DEWI) that can help water resource managers to anticipate droughts so that preparations can be made to mitigate the impact of water shortages. This study employs the expected-deficit-rate of normal water supply conditions as the drought early warning index. An annual-use-reservoir-based water supply system in southern Taiwan was selected as the case study. The water supply simulation was based on reservoir storage at the evaluation time and the reservoir inflow series to cope with the actual water supply process until the end of the hydrologic year. A variety of deficits could be realized during different hydrologic years of records and assumptions of initial reservoir storage. These deficits are illustrated using the Average Shortage Rate (ASR) and the value of the ASR, namely the DEWI. The ASR is divided into 5 levels according to 5 deficit-tolerance combinations of each kind of annual demand. A linear regression model and a Neuro-Fuzzy Computing Technique model were employed to estimate the DEWI using selected factors deduced from supply-demand traits and available information, including: rainfall, reservoir inflow and storage data. The chosen methods mentioned above are used to explain a significant index is useful for both model development and decision making. Tests in the Tsengwen-Wushantou reservoir system showed this DEWI to perform very well in adopting the proper mitigation policy at the end of the wet season.

A new precipitation and drought climatology based on weather patterns.

PubMed

Richardson, Douglas; Fowler, Hayley J; Kilsby, Christopher G; Neal, Robert

2018-02-01

Weather-pattern, or weather-type, classifications are a valuable tool in many applications as they characterize the broad-scale atmospheric circulation over a given region. This study analyses the aspects of regional UK precipitation and meteorological drought climatology with respect to a new set of objectively defined weather patterns. These new patterns are currently being used by the Met Office in several probabilistic forecasting applications driven by ensemble forecasting systems. Weather pattern definitions and daily occurrences are mapped to Lamb weather types (LWTs), and parallels between the two classifications are drawn. Daily precipitation distributions are associated with each weather pattern and LWT. Standardized precipitation index (SPI) and drought severity index (DSI) series are calculated for a range of aggregation periods and seasons. Monthly weather-pattern frequency anomalies are calculated for SPI wet and dry periods and for the 5% most intense DSI-based drought months. The new weather-pattern definitions and daily occurrences largely agree with their respective LWTs, allowing comparison between the two classifications. There is also broad agreement between weather pattern and LWT changes in frequencies. The new data set is shown to be adequate for precipitation-based analyses in the UK, although a smaller set of clustered weather patterns is not. Furthermore, intra-pattern precipitation variability is lower in the new classification compared to the LWTs, which is an advantage in this context. Six of the new weather patterns are associated with drought over the entire UK, with several other patterns linked to regional drought. It is demonstrated that the new data set of weather patterns offers a new opportunity for classification-based analyses in the UK.

A new precipitation and drought climatology based on weather patterns

PubMed Central

Fowler, Hayley J.; Kilsby, Christopher G.; Neal, Robert

2017-01-01

ABSTRACT Weather‐pattern, or weather‐type, classifications are a valuable tool in many applications as they characterize the broad‐scale atmospheric circulation over a given region. This study analyses the aspects of regional UK precipitation and meteorological drought climatology with respect to a new set of objectively defined weather patterns. These new patterns are currently being used by the Met Office in several probabilistic forecasting applications driven by ensemble forecasting systems. Weather pattern definitions and daily occurrences are mapped to Lamb weather types (LWTs), and parallels between the two classifications are drawn. Daily precipitation distributions are associated with each weather pattern and LWT. Standardized precipitation index (SPI) and drought severity index (DSI) series are calculated for a range of aggregation periods and seasons. Monthly weather‐pattern frequency anomalies are calculated for SPI wet and dry periods and for the 5% most intense DSI‐based drought months. The new weather‐pattern definitions and daily occurrences largely agree with their respective LWTs, allowing comparison between the two classifications. There is also broad agreement between weather pattern and LWT changes in frequencies. The new data set is shown to be adequate for precipitation‐based analyses in the UK, although a smaller set of clustered weather patterns is not. Furthermore, intra‐pattern precipitation variability is lower in the new classification compared to the LWTs, which is an advantage in this context. Six of the new weather patterns are associated with drought over the entire UK, with several other patterns linked to regional drought. It is demonstrated that the new data set of weather patterns offers a new opportunity for classification‐based analyses in the UK. PMID:29456290

Drought-sensitive aquifer settings in southeastern Pennsylvania

USGS Publications Warehouse

Zimmerman, Tammy M.; Risser, Dennis W.

2005-01-01

This report describes the results of a study conducted by the U.S. Geological Survey, in cooperation with the Pennsylvania Department of Conservation and Natural Resources, Bureau of Topographic and Geologic Survey, to determine drought-sensitive aquifer settings in southeastern Pennsylvania. Because all or parts of southeastern Pennsylvania have been in drought-warning or drought-emergency status during 6 of the past 10 years from 1994 through 2004, this information should aid well owners, drillers, and water-resource managers in guiding appropriate well construction and sustainable use of Pennsylvania's water resources. 'Drought-sensitive' aquifer settings are defined for this study as areas unable to supply adequate quantities of water to wells during drought. Using information from previous investigations and a knowledge of the hydrogeology and topography of the study area, drought-sensitive aquifer settings in southeastern Pennsylvania were hypothesized as being associated with two factors - a water-table decline (WTD) index and topographic setting. The WTD index is an estimate of the theoretical water-table decline at the ground-water divide for a hypothetical aquifer with idealized geometry. The index shows the magnitude of ground-water decline after cessation of recharge is a function of (1) distance from stream to divide, (2) ground-water recharge rate, (3) transmissivity, (4) specific yield, and (5) duration of the drought. WTD indices were developed for 39 aquifers that were subsequently grouped into categories of high, moderate, and low WTD index. Drought-sensitive settings determined from the hypothesized factors were compared to locations of wells known to have been affected (gone dry, replaced, or deepened) during recent droughts. Information collected from well owners, drillers, and public agencies identified 2,016 wells affected by drought during 1998-2002. Most of the available data on the location of drought-affected wells in the study area were from Chester and Montgomery Counties because those counties have well-construction regulations that identify wells that failed during drought. The locations of drought-affected wells in Chester and Montgomery Counties indicated the most highly sensitive settings are uplands and slopes in aquifers with high WTD index and uplands in aquifers with moderate WTD index. The least sensitive settings are in aquifers with low WTD index, in valleys, or on slopes. A map was developed showing the relative drought sensitivity (low, moderate, and high) of aquifers in southeastern Pennsylvania. Study results were limited by the inability to obtain much information about the location of drought-affected wells, with the exception of Montgomery and Chester Counties. Also, the construction characteristics (particularly depth) of drought-affected wells generally were not available. Well depth could be used to distinguish between problems caused by shallow well depth (generally less than 100 ft) and those caused by deficiency of the aquifer to supply water. With the exception of owner-derived information from a public survey on drought-affected wells (35 wells), depth data were not obtained. Data from the 35 drought-affected wells indicated most were drilled (not dug) and were completed to depths greater than 100 feet. This finding indicates that the affects of recent droughts in southeastern Pennsylvania were not restricted to shallow dug wells, but also affected deeper drilled wells.

Implications of the 2015 European drought on groundwater storage

NASA Astrophysics Data System (ADS)

Rangecroft, S.; Van Loon, A.; Kumar, R.; Mishra, V.

2016-12-01

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

Development of an Experimental African Drought Monitoring and Seasonal Forecasting System: A First Step towards a Global Drought Information System

NASA Astrophysics Data System (ADS)

Wood, E. F.; Chaney, N.; Sheffield, J.; Yuan, X.

2012-12-01

Extreme hydrologic events in the form of droughts are a significant source of social and economic damage. Internationally, organizations such as UNESCO, the Group on Earth Observations (GEO), and the World Climate Research Programme (WCRP) have recognized the need for drought monitoring, especially for the developing world where drought has had devastating impacts on local populations through food insecurity and famine. Having the capacity to monitor droughts in real-time, and to provide drought forecasts with sufficient warning will help developing countries and international programs move from the management of drought crises to the management of drought risk. While observation-based assessments, such as those produced by the US Drought Monitor, are effective for monitoring in countries with extensive observation networks (of precipitation in particular), their utility is lessened in areas (e.g., Africa) where observing networks are sparse. For countries with sparse networks and weak reporting systems, remote sensing observations can provide the real-time data for the monitoring of drought. More importantly, these datasets are now available for at least a decade, which allows for the construction of a climatology against which current conditions can be compared. In this presentation we discuss the development of our multi-lingual experimental African Drought Monitor (ADM) (see http://hydrology.princeton.edu/~nchaney/ADM_ML). At the request of UNESCO, the ADM system has been installed at AGRHYMET, a regional climate and agricultural center in Niamey, Niger and at the ICPAC climate center in Nairobi, Kenya. The ADM system leverages off our U.S. drought monitoring and forecasting system (http://hydrology.princeton.edu/forecasting) that uses the NLDAS data to force the VIC land surface model (LSM) at 1/8th degree spatial resolution for the estimation of our soil moisture drought index (Sheffield et al., 2004). For the seasonal forecast of drought, CFSv2 climate forecasts are bias corrected, downscaled and used as inputs to the VIC LSM as well as forecasts based on ESP and CPC official seasonal outlook. For Africa, data from a combination of remote sensing (TMPA-based precipitation, land cover characteristics) and GFS analysis fields (temperature and wind) are used to monitor drought using our soil moisture drought index as well as 1, 3 and and 6-month SPI. River discharge is also estimated at over 900 locations. Seasonal forecasts have been developed using CFSv2 climate forecasts following the approaches used over CONUS. We will discuss the performance of the system to evaluate the depiction of drought over various scales, from regional to the African continent, and over a number of years to capture multiple drought events. Furthermore, the hindcasts from the seasonal drought forecast system are analyzed to assess the ability of seasonal climate models to detect drought on-set and its recovery. Finally, we will discuss whether our ADM provides a pathway to a Global Drought Information System, a goal of the WCRP Drought Task Force.

Drought impacts on cereal yields in Iberia

NASA Astrophysics Data System (ADS)

Gouveia, Célia; Liberato, Margarida L. R.; Russo, Ana; Montero, Irene

2014-05-01

In the present context of climate change, land degradation and desertification it becomes crucial to assess the impact of droughts to determine the environmental consequences of a potential change of climate. Large drought episodes in Iberian Peninsula have widespread ecological and environmental impacts, namely in vegetation dynamics, resulting in significant crop yield losses. During the hydrological years of 2004/2005 and 2011/2012 Iberia was affected by two extreme drought episodes (Garcia-Herrera et al., 2007; Trigo et al., 2013). This work aims to analyze the spatial and temporal behavior of climatic droughts at different time scales using spatially distributed time series of drought indicators, such as the Standardized Precipitation Evapotranspiration Index (SPEI) (Vicente-Serrano et al., 2010). This climatic drought index is based on the simultaneous use of precipitation and temperature. We have used CRU TS3 dataset to compute SPEI and the Standardized Precipitation Index (SPI). Results will be analyzed in terms of the mechanisms that are responsible by these drought events and will also be used to assess the impact of droughts in crops. Accordingly an analysis is performed to evaluate the large-scale conditions required for a particular extreme anomaly of long-range transport of water vapor from the subtropics. We have used the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA Interim reanalyses, namely, the geopotential height fields, temperature, wind, divergence data and the specific humidity at all pressure levels and mean sea level pressure (MSLP) and total column water vapor (TCWV) for the Euro-Atlantic sector (100°W to 50°E, 0°N-70°N) at full temporal (six hourly) and spatial (T255; interpolated to 0.75° regular horizontal grid) resolutions available to analyse the large-scale conditions associated with the drought onset. Our analysis revealed severe impacts on cereals crop productions and yield (namely wheat) for Portugal and Spain in both considered drought events, however slightly less severe for 2012 than for 2005. In conclusion, and from an operational point of view, our results reveal the ability of the developed methodology to monitor droughts' impacts on crops productions and yields in Iberia. Acknowledgments: This work was partially supported by national funds through FCT (Fundação para a Ciência e a Tecnologia, Portugal) under project QSECA (PTDC/AAG-GLO/4155/2012) Garcia-Herrera R., Paredes D., Trigo R. M., Trigo I. F., Hernandez E., Barriopedro D. and Mendes M. A., 2007: The Outstanding 2004/05 Drought in the Iberian Peninsula: Associated Atmospheric Circulation, J. Hydrometeorol., 8, 483-498. Vicente-Serrano, Sergio M., Santiago Beguería, Juan I. López-Moreno, 2010: A Multiscalar Drought Index Sensitive to Global Warming: The Standardized Precipitation Evapotranspiration Index. J. Climate, 23, 1696-1718. Trigo R.M., Añel J., Barriopedro D., García-Herrera R., Gimeno L., Nieto R., Castillo R., Allen M.R., Massey N. (2013), The record Winter drought of 2011-12 in the Iberian Peninsula [in "Explaining Extreme Events of 2012 from a Climate Perspective". [Peterson, T. C., M. P. Hoerling, P.A. Stott and S. Herring, Eds.] Bulletin of the American Meteorological Society, 94 (9), S41-S45.

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 economic relations, increasing the time factors effectiveness of decision support system. This methodology will be extendable for other Central European countries when country specific data are available and entered into the system. This new drought risk monitoring and forecasting method is an improvement for hydrologists, meteorologists and farmers, allowing to set up a complex drought monitoring system, where for a given period and respective catchment area the expected yield loss can be predicted, and the role of vegetation in the hydrological cycle could be more precisely quantified. Based on the results more water-saving agricultural land use alternatives could be planned on drought areas.

Analysis of potential future droughts limiting maize production, in the Luvuvhu River catchment area, South Africa

NASA Astrophysics Data System (ADS)

Masupha, Teboho Elisa; Moeletsi, Mokhele Edmond

2018-06-01

Recurring droughts associated with global warming have raised major concern for the agricultural sector, particularly vulnerable small-scale farmers who rely on rain-fed farming such as in the Luvuvhu River catchment. The Standardized Precipitation Evapotranspiration Index (SPEI) and Water Requirement Satisfaction Index (WRSI) were calculated to assess drought on a 120-day maturing maize crop based on outputs of the CSIRO-Mk3.6.0 under RCP 4.5 emission scenario, for the period 1980/81-2089/90. Results by SPEI show that 40-54% of the agricultural seasons during the base period experienced mild drought conditions (SPEI 0 to -0.99), equivalent to a recurrence of once in two seasons. However, WRSI results clearly indicated that stations in the drier regions (annual rainfall <600 mm) of the catchment experienced mild drought (WRSI 70 - 79) corresponding to satisfactory crop performance every season. Results further showed overall mild to moderate droughts in the beginning of the near-future climate period (2020/21-2036/37) with SPEI values not decreasing below -1.5. These conditions are then expected to change during the far-future climate period (2055/56-2089/90), whereby results on the expected crop performance predicted significantly drier conditions (p < 0.05). This study provided information on how farmers in the area can prepare for future agricultural seasons, while there is sufficient time to implement strategies to reduce drought risk potential. Thus, integrated interventions could provide best options for improving livelihoods and building the capability of farmers to manage climate change-related stresses.

[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.

Value of Adaptive Drought Forecasting and Management for the ACF River Basin in the Southeast U.S.

NASA Astrophysics Data System (ADS)

Georgakakos, A. P.; Kistenmacher, M.

2016-12-01

In recent times, severe droughts in the southeast U.S. occur every 6 to 10 years and last for up to 4 years. During such drought episodes, the ACF River Basin supplies decline by up to 50 % of their normal levels, and water stresses increase rather markedly, exacerbating stakeholder anxiety and conflicts. As part of the ACF Stakeholder planning process, GWRI has developed new tools and carried out comprehensive assessments to provide quantitative answers to several important questions related to drought prediction and management: (i) Can dry and wet climatic periods be reliably anticipated with sufficiently long lead times? What drought indices can support reliable, skillful, and long-lead forecasts? (ii) What management objectives can seasonal climate forecasts benefit? How should benefits/impacts be shared? (iii) What operational adjustments are likely to mitigate stakeholder impacts or increase benefits consistent with stakeholder expectations? Regarding drought prediction, a large number of indices were defined and tested at different basin locations and lag times. These included local/cumulative unimpaired flows (UIFs) at 10 river nodes; Mean Areal Precipitation (MAP); Standard Precipitation Index (SPI); Palmer Drought Severity Index; Palmer Modified Drought Index; Palmer Z-Index; Palmer Hydrologic Drought Severity Index; and Soil Moisture—GWRI watershed model. Our findings show that all ACF sub-basins exhibit good forecast skill throughout the year and with sufficient lead time. Index variables with high explanatory value include: previous UIFs, soil moisture states (generated by the GWRI watershed model), and PDSI. Regarding drought management, assessments with coupled forecast-management schemes demonstrate that the use of adaptive forecast-management procedures improves reservoir operations and meets basin demands more reliably. Such improvements can support better management of lake levels, higher environmental and navigation flows, higher dependable power generation hours, and better management of consumptive uses without adverse impacts on other stakeholder interests. However, realizing these improvements requires (1) usage of adaptive reservoir management procedures (incorporating forecasts), and (2) stakeholder agreement on equitable benefit sharing.

Drought monitoring and assessment: Remote sensing and modeling approaches for the Famine Early Warning Systems Network

USGS Publications Warehouse

Senay, Gabriel; Velpuri, Naga Manohar; Bohms, Stefanie; Budde, Michael; Young, Claudia; Rowland, James; Verdin, James

2015-01-01

Drought monitoring is an essential component of drought risk management. It is usually carried out using drought indices/indicators that are continuous functions of rainfall and other hydrometeorological variables. This chapter presents a few examples of how remote sensing and hydrologic modeling techniques are being used to generate a suite of drought monitoring indicators at dekadal (10-day), monthly, seasonal, and annual time scales for several selected regions around the world. Satellite-based rainfall estimates are being used to produce drought indicators such as standardized precipitation index, dryness indicators, and start of season analysis. The Normalized Difference Vegetation Index is being used to monitor vegetation condition. Several satellite data products are combined using agrohydrologic models to produce multiple short- and long-term indicators of droughts. All the data sets are being produced and updated in near-real time to provide information about the onset, progression, extent, and intensity of drought conditions. The data and products produced are available for download from the Famine Early Warning Systems Network (FEWS NET) data portal at http://earlywarning.usgs.gov. The availability of timely information and products support the decision-making processes in drought-related hazard assessment, monitoring, and management with the FEWS NET. The drought-hazard monitoring approach perfected by the U.S. Geological Survey for FEWS NET through the integration of satellite data and hydrologic modeling can form the basis for similar decision support systems. Such systems can operationally produce reliable and useful regional information that is relevant for local, district-level decision making.

Relationship Between Palmer's Drought Severity Index and the Moisture Index of Woody Debris in the Southern Coastal Plain

Treesearch

James D. Haywood; Richard H. Stagg; Allan E. Tiarks

2004-01-01

After the 1998 through 2000 drought in Louisiana, some prescribed burns had uncommonly severe fire behavior. A significant portion of the consumed fuels most likely were larger material normally unavailable for burning. Therefore at sites in Louisiana, Mississippi, and Texas, we studied the relationship between Palmer’s Drought Severity Index (PDSI) and the drying rate...

Evidence for increasingly variable Palmer Drought Severity Index in the United States since 1895.

PubMed

Rayne, Sierra; Forest, Kaya

2016-02-15

Annual and summertime trends towards increasingly variable values of the Palmer Drought Severity Index (PDSI) over a sub-decadal period (five years) were investigated within the contiguous United States between 1895 and the present. For the contiguous United States as a whole, there is a significant increasing trend in the five-year running minimum-maximum ranges for the annual PDSI (aPDSI5 yr(min|max, range)). During this time frame, the average aPDSI5 yr(min|max, range) has increased by about one full unit, indicating a substantial increase in drought variability over short time scales across the United States. The end members of the running aPDSI5 yr(min|max, range) highlight even more rapid changes in the drought index variability within the past 120 years. This increasing variability in the aPDSI5 yr(min|max, range) is driven primarily by changes taking place in the Pacific and Atlantic Ocean coastal climate regions, climate regions which collectively comprise one-third the area of the contiguous United States. Similar trends were found for the annual and summertime Palmer Hydrological Drought Index (PHDI), the Palmer Modified Drought Index (PMDI), and the Palmer Z Index (PZI). Overall, interannual drought patterns in the contiguous United States are becoming more extreme and difficult to predict, posing a challenge to agricultural and other water-resource related planning efforts. Copyright © 2015 Elsevier B.V. All rights reserved.

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

PubMed

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

2014-10-09

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

A new drought tipping point for conifer mortality

NASA Astrophysics Data System (ADS)

Kolb, Thomas E.

2015-03-01

(Huang et al 2015 Environ. Res. Lett. 10 024011) present a method for predicting mortality of ponderosa pine (Pinus ponderosa) and pinyon pine (Pinus edulis) in the Southwestern US during severe drought based on the relationship between the standardized precipitation-evapotranspiration index (SPEI) and annual tree ring growth. Ring growth was zero when SPEI for September to July was -1.64. The threshold SPEI of -1.64 was successful in distinguishing areas with high tree mortality during recent severe drought from areas with low mortality, and is proposed to be a tipping point of drought severity leading to tree mortality. Below, I discuss this work in more detail.

A global examination of the response of ecosystem water-use efficiency to drought based on MODIS data.

PubMed

Huang, Ling; He, Bin; Han, Le; Liu, Junjie; Wang, Haiyan; Chen, Ziyue

2017-12-01

Ecosystem water-use efficiency (WUE) plays an important role in carbon and water cycles. Currently, the response of WUE to drought disturbance remains controversial. Based on the global ecosystem gross primary productivity (GPP) product and the evapotranspiration product (ET), both of which were retrieved from the moderate resolution imaging spectroradiometer (MODIS), as well as the drought index, this study comprehensively examined the relationship between ecosystem WUE (WUE=GPP/ET) and drought at the global scale. The response of WUE to drought showed large differences in various regions and biomes. WUE for arid ecosystems typically showed a negative response to drought, whereas WUE for humid ecosystems showed both positive and negative response to drought. Legacy effects of drought on ecosystem WUE were observed. Furthermore, ecosystems showed a sensitive response to abrupt changes in hydrological climatic conditions. The transition from wet to dry years should increase ecosystem WUE, and the opposite change in WUE should occur when an ecosystem experiences a transition from dry to wet years. This indicates the resilience of ecosystems to drought disturbance. Knowledge from this study should provide an in-depth understanding of ecosystem strategies for coping with drought. Copyright © 2017 Elsevier B.V. All rights reserved.

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 been accessed for the agricultural data at the county level. Preliminary analyses show that large parts of Midwest and Southern parts of Florida and California are prone to multiyear droughts. This can primarily be attributed to high agricultural and/or urban water demands coupled with high interannual variability in supply. We propose to develop season-ahead and monthly updated forecasts of the drought index for informing the drought management plans. Given the already customized (sector specific) nature of the proposed drought index and its ability to represent the variability in both supply and demand, the early warning or forecasting of the index would not only complement the drought early warning systems in place by the national integrated drought information system (NIDIS) but also help in prescribing the ameliorative measures for adaptation.

Threshold determination and hazard evaluation of the disaster about drought/flood sudden alternation in Huaihe River basin, China

NASA Astrophysics Data System (ADS)

Ji, Zhonghui; Li, Ning; Wu, Xianhua

2017-08-01

Based on the related impact factors of precipitation anomaly referred in previous research, eight atmospheric circulation indicators in pre-winter and spring picked out by correlation analysis as the independent variables and the hazard levels of drought/flood sudden alternation index (DFSAI) as the dependent variables were used to construct the nonlinear and nonparametric classification and regression tree (CART) for the threshold determination and hazard evaluation on bimonthly and monthly scales in Huaihe River basin. Results show that the spring indicators about Arctic oscillation index (AOI_S), Asia polar vortex area index (APVAI_S), and Asian meridional circulation index (AMCI_S) were extracted as the three main impact factors, which were proved to be suitable for the hazard levels assessment of the drought/flood sudden alternation (DFSA) disaster based on bimonthly scale. On monthly scale, AOI_S, northern hemisphere polar vortex intensity index in pre-winter (NHPVII_PW), and AMCI_S are the three primary variables in hazard level prediction of DFSA in May and June; NHPVII_PW, AMCI_PW, and AMCI_S are for that in June and July; NHPVII_PW and EASMI are for that in July and August. The type of the disaster (flood to drought/drought to flood/no DFSA) and hazard level under different conditions also can be obtained from each model. The hazard level and type were expressed by the integer from - 3 to 3, which change from the high level of disaster that flood to drought (level - 3) to the high level of the reverse type (level 3). The middle number 0 represents no DFSA. The high levels of the two sides decrease progressively to the neutralization (level 0). When AOI_S less than - 0.355, the disaster of the quick turn from drought to flood is more apt to happen (level 1) on bimonthly scale; when AOI_S less than - 1.32, the same type disaster may occur (level 2) in May and June on monthly scale. When NHPVII_PW less than 341.5, the disaster of the quick turn from flood to drought will occur (level - 1) in June and July on monthly scale. By this analogy, different hazard types and levels all can be judged from the optimal models. The corresponding data from 2011 to 2015 were selected to verify the final models through the comparison between the predicted and actual levels, and the models of M1 (bimonthly scale), M2, and M3 (monthly scale) were proved to be acceptable by the prediction accuracy rate (compared the predicted with the observed levels, 73%, 11/15). The proposed CART method in this research is a new try for the short-term climate prediction.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Designing basin-customized combined drought indices via feature extraction

NASA Astrophysics Data System (ADS)

Zaniolo, Marta; Giuliani, Matteo; Castelletti, Andrea

2017-04-01

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

Characterization of drought patterns through remote sensing over The Chihuahua Desert, Mexico"

NASA Astrophysics Data System (ADS)

Madrigal, J. M.; Lopez, A.; Garatuza, J.

2013-12-01

Drought is a phenomenon that has intensified during the last few decades in the arid and semi-arid zones of northern Mexico. In the Chihuahua desert, across Chihuahua, Durango and Coahuila states has caused loss of food sustainability (agriculture, livestock), an increase in human health problems, and detriment of ecosystem services as well as important economic losses. In order to understand this phenomenon, it is necessary to create tools that allow monitoring the territory's spatial heterogeneity and multi-temporality. With this purpose we propose the implementation of a drought model which includes the traditional indexes of climatic drought, such as the Palmer Drought Severity Index PDSI, the Standardized Index of Rainfall SPI, data from meteorological stations and biophysical variations obtained from the MODIS sensors product MOD13 NDVI from 2001 to 2010, as well as biophysical variables characteristic of the environment, such as land use and vegetation coverage, Eco-regions, soil moisture, digital elevation model and irrigate agriculture districts. With the MODIS images, a spatially coherent time series was created analyzing the study area's phenology (TIMESAT) created the Seasonal Greenness (SG) and Start of Season Anomaly (SOSA) for the mentioned nine years. Through this, the annual cycles were established. With a decision tree model, all the previously mentioned proposed variables were integrated. The proposed model produces a general map which characterizes the vegetation condition (extreme drought, severe drought, moderate drought, near normal). Even though different techniques have been proposed on the monitoring of droughts, most of them generate drought indexes with a spatial resolution of 1km (Wardlow, B. et. al 2008; Levent T. et al. 2013). One of the main concerns of researchers on the matter is on improving the spatial information content and on having a better representation of the phenomenon. We use the normalized difference vegetation index (NDVI) data acquired by MODIS instead of the Advanced Very High Resolution Radiometer (AVHRR). The results show a better drought pattern characterization over The Chihuahua Desert, Mexico". The future work will consist of making a sensibility and optimization study of the variables used in the CART model, including others such as evapotranspiration and rainfall. Additionally, this work will research on the potential of using Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI).

Evaluation of groundwater droughts in Austria

NASA Astrophysics Data System (ADS)

Haas, Johannes Christoph; Birk, Steffen

2015-04-01

Droughts are abnormally dry periods that affect various aspects of human life on earth, ranging from negative impacts on agriculture or industry, to being the cause for conflict and loss of human life. The changing climate reinforces the importance of investigations into this phenomenon. Various methods to analyze and classify droughts have been developed. These include drought indices such as the Standard Precipitation Index SPI, the Palmer Drought Severity Index PDSI or the Crop Moisture Index CMI. These and other indices consider meteorological parameters and/or their effects on soil moisture. A depletion of soil moisture triggered by low precipitation and high evapotranspiration may also cause reduced groundwater recharge and thus decreasing groundwater levels and reduced groundwater flow to springs, streams, and wetlands. However, the existing indices were generally not designed to address such drought effects on groundwater. Thus, a Standardized Groundwater level Index has recently been proposed by Bloomfied and Marchant (2013). Yet, to our knowledge, this approach has only been applied to consolidated aquifers in the UK. This work analyzes time series of groundwater levels from various, mostly unconsolidated aquifers in Austria in order to characterize the effects of droughts on aquifers in different hydrogeologic and climatic settings as well as under different usage scenarios. In particular, comparisons are made between the water rich Alpine parts of Austria, and the dryer parts situated in the East. The time series of groundwater levels are compared to other data, such as meteorological time series and written weather records about generally accepted phenomena, such as the 2003 European drought and heat wave. Thus, valuable insight is gained into the propagation of meteorological droughts through the soil and the aquifer in different types of hydrogeologic and climatic settings, which provides a prerequisite for the assessment of the aquifers' drought susceptibility in a changing climate. References: Bloomfield, J. P. & Marchant, B. P. Analysis of groundwater drought building on the standardised precipitation index approach Hydrology and Earth System Sciences, 2013, 17, 4769-4787

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

PubMed

Amirataee, Babak; Montaseri, Majid; Rezaie, Hossein

2018-01-15

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

Effects of meteorological droughts on agricultural water resources in southern China

NASA Astrophysics Data System (ADS)

Lu, Houquan; Wu, Yihua; Li, Yijun; Liu, Yongqiang

2017-05-01

With the global warming, frequencies of drought are rising in the humid area of southern China. In this study, the effects of meteorological drought on the agricultural water resource based on the agricultural water resource carrying capacity (AWRCC) in southern China were investigated. The entire study area was divided into three regions based on the distributions of climate and agriculture. The concept of the maximum available water resources for crops was used to calculate AWRCC. Meanwhile, an agricultural drought intensity index (ADI), which was suitable for rice planting areas, was proposed based on the difference between crop water requirements and precipitation. The actual drought area and crop yield in drought years from 1961 to 2010 were analyzed. The results showed that ADI and AWRCC were significantly correlated with the actual drought occurrence area and food yield in the study area, which indicated ADI and AWRCC could be used in drought-related studies. The effects of seasonal droughts on AWRCC strongly depended on both the crop growth season and planting structure. The influence of meteorological drought on agricultural water resources was pronounced in regions with abundant water resources, especially in Southwest China, which was the most vulnerable to droughts. In Southwest China, which has dry and wet seasons, reducing the planting area of dry season crops and rice could improve AWRCC during drought years. Likewise, reducing the planting area of double-season rice could improve AWRCC during drought years in regions with a double-season rice cropping system. Our findings highlight the importance of adjusting the proportions of crop planting to improve the utilization efficiency of agricultural water resources and alleviate drought hazards in some humid areas.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Fuzzy rule-based forecast of meteorological drought in western Niger

NASA Astrophysics Data System (ADS)

Abdourahamane, Zakari Seybou; Acar, Reşat

2018-01-01

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

Dynamic drought risk assessment using crop model and remote sensing techniques

NASA Astrophysics Data System (ADS)

Sun, H.; Su, Z.; Lv, J.; Li, L.; Wang, Y.

2017-02-01

Drought risk assessment is of great significance to reduce the loss of agricultural drought and ensure food security. The normally drought risk assessment method is to evaluate its exposure to the hazard and the vulnerability to extended periods of water shortage for a specific region, which is a static evaluation method. The Dynamic Drought Risk Assessment (DDRA) is to estimate the drought risk according to the crop growth and water stress conditions in real time. In this study, a DDRA method using crop model and remote sensing techniques was proposed. The crop model we employed is DeNitrification and DeComposition (DNDC) model. The drought risk was quantified by the yield losses predicted by the crop model in a scenario-based method. The crop model was re-calibrated to improve the performance by the Leaf Area Index (LAI) retrieved from MODerate Resolution Imaging Spectroradiometer (MODIS) data. And the in-situ station-based crop model was extended to assess the regional drought risk by integrating crop planted mapping. The crop planted area was extracted with extended CPPI method from MODIS data. This study was implemented and validated on maize crop in Liaoning province, China.

Drought variability and change across the Iberian Peninsula

NASA Astrophysics Data System (ADS)

Coll, J. R.; Aguilar, E.; Ashcroft, L.

2017-11-01

Drought variability and change was assessed across the Iberian Peninsula over more than 100 years expanding through the twentieth century and the first decade of the twenty-first century. Daily temperature and precipitation data from 24 Iberian time series were quality controlled and homogenized to create the Monthly Iberian Temperature and Precipitation Series (MITPS) for the period 1906-2010. The Standardized Precipitation Index (SPI), driven only by precipitation, and the Standardized Precipitation Evapotranspiration Index (SPEI), based on the difference between the precipitation and the reference evapotranspiration (ET0), were computed at annual and seasonal scale to describe the evolution of droughts across time. The results confirmed that a clear temperature increase has occurred over the entire Iberian Peninsula at the annual and seasonal scale, but no significant changes in precipitation accumulated amounts were found. Similar drought variability was provided by the SPI and SPEI, although the SPEI showed greater drought severity and larger surface area affected by drought than SPI from 1980s to 2010 due to the increase in atmospheric evaporative demand caused by increased temperatures. Moreover, a clear drying trend was found by the SPEI for most of the Iberian Peninsula at annual scale and also for spring and summer, although the SPI did not experience significant changes in drought conditions. From the drying trend identified for most of the Iberian Peninsula along the twentieth century, an increase in drought conditions can also be expected for this region in the twenty-first century according to future climate change projections and scenarios.

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

PubMed

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

2013-01-15

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

Drought Effects on Riparian Vegetation in the Santa Clara River Basin Using Airborne Imaging Spectroscopy

NASA Astrophysics Data System (ADS)

Schmidt, C.; Miller, D.; Roberts, D. A.

2017-12-01

Riparian forests are groundwater-dependent ecosystems that are highly sensitive to changes in the water table. As climate change continues, droughts are likely to become more frequent and severe in Southern California, threatening the persistence of these ecosystems. From 2012 to 2017, California experienced the most severe drought in the past century, providing a case study to assess drought impacts. Using imagery collected by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) from 2013 and 2016, we evaluated changes in riparian forest health in a central section of the Santa Clara River Basin, a multi-use river located just north of Los Angeles. We used Constrained Reference Endmember Selection (CRES) to select reference endmembers of green vegetation (GV), non-photosynthetic vegetation (NPV), and rock/soil. We used spectral mixture analysis to estimate endmember fractions. We assessed changes in green vegetation cover and canopy water content at key monitoring sites based on the Relative GV Fraction, the Normalized Difference Water Index, and the Water Band Index. Preliminary results showed a decrease in the GV fraction and an increase in the NPV fraction, indicating an overall decline in riparian forest health as a result of drought. Our results demonstrate the spatial extent of drought effects in groundwater dependent ecosystems.

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.

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.

Effects of Geographic Diversification on Risk Pooling to Mitigate Drought-Related Financial Losses for Water Utilities

NASA Astrophysics Data System (ADS)

Baum, Rachel; Characklis, Gregory W.; Serre, Marc L.

2018-04-01

As the costs and regulatory barriers to new water supply development continue to rise, drought management strategies have begun to rely more heavily on temporary conservation measures. While these measures are effective, they often lead to intermittent and unpredictable reductions in revenues that are financially disruptive to water utilities, raising concerns over lower credit ratings and higher rates of borrowing for this capital intensive sector. Consequently, there is growing interest in financial risk management strategies that reduce utility vulnerabilities. This research explores the development of financial index insurance designed to compensate a utility for drought-related losses. The focus is on analyzing candidate hydrologic indices that have the potential to be used by utilities across the US, increasing the potential for risk pooling, which would offer the possibility of both lower risk management costs and more widespread implementation. This work first analyzes drought-related financial risks for 315 publicly operated water utilities across the country and examines the effectiveness of financial contracts based on several indices both in terms of their correlation with utility revenues and their spatial autocorrelation across locations. Hydrologic-based index insurance contracts are then developed and tested over a 120 year period. Results indicate that risk pooling, even under conditions in which droughts are subject to some level of spatial autocorrelation, has the potential to significantly reduce the cost of managing financial risk.

An assessment of three measures of long-term moisture deficiency before critical fire periods.

Treesearch

Donald A. Haines; Von J. Johnson; William A. Main

1976-01-01

Values of the Palmer Drought Index, the Keetch-Byram Drought Index, and a Buildup Index are calculated for 26 critical fires situations in the north-central and north-eastern states. The paper examines the response characteristics of these indexes, representative of different moisture regimes, relative to fire danger.

Drought forecasting in eastern Australia using multivariate adaptive regression spline, least square support vector machine and M5Tree model

NASA Astrophysics Data System (ADS)

Deo, Ravinesh C.; Kisi, Ozgur; Singh, Vijay P.

2017-02-01

Drought forecasting using standardized metrics of rainfall is a core task in hydrology and water resources management. Standardized Precipitation Index (SPI) is a rainfall-based metric that caters for different time-scales at which the drought occurs, and due to its standardization, is well-suited for forecasting drought at different periods in climatically diverse regions. This study advances drought modelling using multivariate adaptive regression splines (MARS), least square support vector machine (LSSVM), and M5Tree models by forecasting SPI in eastern Australia. MARS model incorporated rainfall as mandatory predictor with month (periodicity), Southern Oscillation Index, Pacific Decadal Oscillation Index and Indian Ocean Dipole, ENSO Modoki and Nino 3.0, 3.4 and 4.0 data added gradually. The performance was evaluated with root mean square error (RMSE), mean absolute error (MAE), and coefficient of determination (r2). Best MARS model required different input combinations, where rainfall, sea surface temperature and periodicity were used for all stations, but ENSO Modoki and Pacific Decadal Oscillation indices were not required for Bathurst, Collarenebri and Yamba, and the Southern Oscillation Index was not required for Collarenebri. Inclusion of periodicity increased the r2 value by 0.5-8.1% and reduced RMSE by 3.0-178.5%. Comparisons showed that MARS superseded the performance of the other counterparts for three out of five stations with lower MAE by 15.0-73.9% and 7.3-42.2%, respectively. For the other stations, M5Tree was better than MARS/LSSVM with lower MAE by 13.8-13.4% and 25.7-52.2%, respectively, and for Bathurst, LSSVM yielded more accurate result. For droughts identified by SPI ≤ - 0.5, accurate forecasts were attained by MARS/M5Tree for Bathurst, Yamba and Peak Hill, whereas for Collarenebri and Barraba, M5Tree was better than LSSVM/MARS. Seasonal analysis revealed disparate results where MARS/M5Tree was better than LSSVM. The results highlight the importance of periodicity in drought forecasting and also ascertains that model accuracy scales with geographic/seasonal factors due to complexity of drought and its relationship with inputs and data attributes that can affect the evolution of drought events.

Drought Events and Their Impacts on Food Production in New Zealand: Historical Analysis and Outlook Model Development

NASA Astrophysics Data System (ADS)

Li, Y.; Yin, C.; Urich, P.; Hill, R.

2012-12-01

Given the importance of the primary production sector, climatic conditions have always been a significant driver of food production in New Zealand. The country has experienced a number of severe droughts throughout its history, where a number of extended periods of low rainfall have severely impacted primary production. The characteristics of historical drought and their impacts on the primary production sector are analysed, including the economic losses in the 1998-1999 and 2007-2009 events. We include the analysis of a set of national standardised drought monitoring indices: Standardised Precipitation Index (SPI), Standardised Precipitation Evapotranspiration Index (SPEI), Soil moisture Index (SMI), and Standardised Pasture Growth Index (SPGI). Since the drought events in New Zealand are clearly linked with ENSO, the SST anomalies in the key regions can be good predictors of drought events. Artificial Neural Network (ANN) information processing technics have been applied to build local drought outlook models, the predictors are the SST anomaly of eight key regions that impact New Zealand climate produced by the Climate Forecasting System v2(CFSv2) of NCEP, and the local NIWA derived observed precipitation and soil moisture data. SST is a variable that CFSv2 can forecast with high skill and after bias correction, can be applied as a climate predictor for New Zealand. Inclusion of local data and the persistent nature of drought leads to good predictors therefore one to three month ensemble drought outlooks can be produced for New Zealand. The potential changes of drought intensity and frequency over the medium to long term future are investigated using downscaled data from 12 GCMs and multiple scenarios. The results indicate that New Zealand may experience more severe drought in many areas, therefore adaptation should be planned and implemented.

Contribution of Anthropogenic Warming to California Drought During 2012-2014

NASA Technical Reports Server (NTRS)

Williams, A. Park; Seager, Richard; Abatzoglou, John T.; Cook, Benjamin I.; Smerdon, Jason E.; Cook, Edward R.

2015-01-01

A suite of climate data sets and multiple representations of atmospheric moisture demand are used to calculate many estimates of the self-calibrated Palmer Drought Severity Index, a proxy for near-surface soil moisture, across California from 1901 to 2014 at high spatial resolution. Based on the ensemble of calculations, California drought conditions were record breaking in 2014, but probably not record breaking in 2012-2014, contrary to prior findings. Regionally, the 2012-2014 drought was record breaking in the agriculturally important southern Central Valley and highly populated coastal areas. Contributions of individual climate variables to recent drought are also examined, including the temperature component associated with anthropogenic warming. Precipitation is the primary driver of drought variability but anthropogenic warming is estimated to have accounted for 8-27 percent of the observed drought anomaly in 2012-2014 and 5-18 percent in 2014. Although natural variability dominates, anthropogenic warming has substantially increased the overall likelihood of extreme California droughts.

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

USGS Publications Warehouse

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

2011-01-01

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

A new precipitation and meteorological drought climatology based on weather patterns

NASA Astrophysics Data System (ADS)

Richardson, D.; Fowler, H. J.; Kilsby, C. G.; Neal, R.

2017-12-01

Weather-pattern, or weather-type, classifications are a valuable tool in many applications as they characterise the broad-scale atmospheric circulation over a given region. An analysis of regional UK precipitation and meteorological drought climatology with respect to a set of objectively defined weather patterns is presented. This classification system, introduced last year, is currently being used by the Met Office in several probabilistic forecasting applications driven by ensemble forecasting systems. The classification consists of 30 daily patterns derived from North Atlantic Ocean and European mean sea level pressure data. Clustering these 30 patterns yields another set of eight patterns that are intended for use in longer-range applications. Weather pattern definitions and daily occurrences are mapped to the commonly-used Lamb Weather Types (LWTs), and parallels between the two classifications are drawn. Daily precipitation distributions are associated with each weather pattern and LWT. Drought index series are calculated for a range of aggregation periods and seasons. Monthly weather-pattern frequency anomalies are calculated for different drought index thresholds, representing dry, wet and drought conditions. The set of 30 weather patterns is shown to be adequate for precipitation-based analyses in the UK, although the smaller set of clustered patterns is not. Furthermore, intra-pattern precipitation variability is lower in the new classification compared to the LWTs, which is an advantage in the context of precipitation studies. Weather patterns associated with drought over the different UK regions are identified. This has potential forecasting application - if a model (e.g. a global seasonal forecast model) can predict weather pattern occurrences then regional drought outlooks may be derived from the forecasted weather patterns.

The complex influence of ENSO on droughts in Ecuador

NASA Astrophysics Data System (ADS)

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

2017-01-01

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

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

NASA Astrophysics Data System (ADS)

Kogan, F.

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

A new index for identifying socioeconomic drought events under climate change over the East River basin in China

NASA Astrophysics Data System (ADS)

Shi, H.; Chen, J.; Wang, K.; Niu, J.

2017-12-01

Drought, which means severe water deficiencies, is a complex natural hazard that may have destructive damages on societal properties and lives. Generally, socioeconomic drought occurs when the water resources systems cannot meet the water demands due to a weather-related shortfall in water supply to societies. This paper aims to propose a new index (i.e., socioeconomic drought index (SEDI)) for identifying socioeconomic drought events on different levels (i.e., slight, moderate, severe and extreme) under climate change through considering the gap between water supply and demand. First, the minimum in-stream water requirement (MWR) is determined through comprehensively considering the requirements of water quality, ecology, navigation and water supply. Second, according to the monthly water deficit calculated as the monthly streamflow data minus the MWR, drought month can be identified. Third, according to the cumulative water deficit derived from the monthly water deficit, drought duration (i.e., the number of continuous drought months) can be detected. Fourth, the SEDI of each socioeconomic drought event can be calculated through integrating the impacts of the cumulative water deficit and drought duration. The study area is the East River basin in South China, and the impact of a multi-year reservoir (i.e., the Xinfengjiang Reservoir) on drought is also analyzed. For historical and future drought analysis, it is concluded that the proposed SEDI is feasible to identify socioeconomic drought events. The results show that a number of socioeconomic drought events (including some extreme ones) may occur during 2020-2099, and the appropriate reservoir operation can significantly ease such situation.

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

NASA Astrophysics Data System (ADS)

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

2017-08-01

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

A seasonal forecast scheme for the Inner Mongolia spring drought part-II: a logical reasoning evidence-based method for spring predictions

NASA Astrophysics Data System (ADS)

Gao, Tao; Wulan, Wulan; Yu, Xiao; Yang, Zelong; Gao, Jing; Hua, Weiqi; Yang, Peng; Si, Yaobing

2018-05-01

Spring precipitation is the predominant factor that controls meteorological drought in Inner Mongolia (IM), China. This study used the anomaly percentage of spring precipitation (PAP) as a drought index to measure spring drought. A scheme for forecasting seasonal drought was designed based on evidence of spring drought occurrence and speculative reasoning methods introduced in computer artificial intelligence theory. Forecast signals with sufficient lead-time for predictions of spring drought were extracted from eight crucial areas of oceans and 500-hPa geopotential height. Using standardized values, these signals were synthesized into three examples of spring drought evidence (SDE) depending on their primary effects on three major atmospheric circulation components of spring precipitation in IM: the western Pacific subtropical high, North Polar vortex, and East Asian trough. Thresholds for the SDE were determined following numerical analyses of the influential factors. Furthermore, five logical reasoning rules for distinguishing the occurrence of SDE were designed after examining all possible combined cases. The degree of confidence in the rules was determined based on estimations of their prior probabilities. Then, an optimized logical reasoning scheme was identified for judging the possibility of spring drought. The scheme was successful in hindcast predictions of 11 of the 16 (accuracy: 68.8%) spring droughts that have occurred during 1960-2009. Moreover, the accuracy ratio for the same period was 82.0% for drought (PAP ≤ -20%) or not (PAP > -20%). Predictions for the recent 6-year period (2010-2015) demonstrated successful outcomes.

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-07-01

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

Drought analysis and water resource availability using standardised precipitation evapotranspiration index

NASA Astrophysics Data System (ADS)

Hui-Mean, Foo; Yusop, Zulkifli; Yusof, Fadhilah

2018-03-01

Trend analysis for potential evapotranspiration (PET) and climatic water balance (CWB) is critical in identifying the wetness or dryness episodes with respect to the water surplus or deficit. The PET is computed based on the monthly average temperature for the entire Peninsular Malaysia using Thornthwaite parameterization. The trends and slope's magnitude for the PET and CWB were then investigated using Mann-Kendall, Spearman's rho tests and Thiel-Sen estimator. The 1-, 3-, 6- and 12-month standardised precipitation evapotranspiration index (SPEI) is applied to determine the drought episodes and the average recurrence interval are calculated based on the SPEI. The results indicate that most of the stations show an upward trend in annual and monthly PET while majority of the regions show an upward trend in annual CWB except for the Pahang state. The increasing trends detected in the CWB describe water is in excess especially during the northeast monsoons while the decreasing trends imply water insufficiency. The excess water is observed mostly in January especially in the west coast, east coast and southwest regions that suggest more water is available for crop requirement. The average recurrence interval for drought episodes is almost the same for the smaller severity with various time scale of SPEI and high probability of drought occurrence is observed for some regions. The findings are useful for policymakers and practitioners to improve water resources planning and management, in particular to minimise drought effects in the future. Future research shall address the influence of topography on drought behaviour using more meteorological stations and to include east Malaysia in the analysis.

The turn-of-the-century drought in North America: The new normal?

NASA Astrophysics Data System (ADS)

Schwalm, C. R.; Williams, C. A.; Schaefer, K. M.; NACP Site Synthesis Team

2011-12-01

At the turn of the century, from 2000 to 2004, western North America (25°-50°N, 100°-125°W) experienced a severe drought with far reaching consequences for the terrestrial biosphere. We quantified the drought's water and carbon cycle implications using upscaled flux tower data, observed and simulated fluxes from the NACP Site Synthesis, remote sensing products, weather reanalysis, crop yield, and river discharge. During the turn of the century drought we found a widespread drydown of the terrestrial biosphere, large decreases in river discharge and greenness, and a ~10% loss in cropland productivity. At the footprint scale carbon uptake declined with an anomalous carbon source of 0.11 Pg C/yr integrated over the full domain. Flux towers also recorded a clear signal of reduced latent and increased sensible heat fluxes, apart from grasslands. Dendrochronological reconstructions of drought extent, duration, and severity, based on the Palmer Drought Severity Index drought metric, indicated that the turn of the century drought was unprecedented since 1200 CE. Predicted changes in precipitation and drought, based on the CMIP3 multi-model mean, could permanently disable the weak sink (NEE = -0.19 Pg C/yr) in western North America by the midpoint of the 21st Century. Projections indicate the turn-of-the-century drought will be wet compared to the latter half of the 21st Century.

[Correlation analysis on normalized difference vegetation index (NDVI) of different vegetations and climatic factors in Southwest China].

PubMed

Zhang, Yuan-Dong; Zhang, Xiao-He; Liu, Shi-Rong

2011-02-01

Based on the 1982-2006 NDVI remote sensing data and meteorological data of Southwest China, and by using GIS technology, this paper interpolated and extracted the mean annual temperature, annual precipitation, and drought index in the region, and analyzed the correlations of the annual variation of NDVI in different vegetation types (marsh, shrub, bush, grassland, meadow, coniferous forest, broad-leaved forest, alpine vegetation, and cultural vegetation) with corresponding climatic factors. In 1982-2006, the NDVI, mean annual temperature, and annual precipitation had an overall increasing trend, and the drought index decreased. Particularly, the upward trend of mean annual temperature was statistically significant. Among the nine vegetation types, the NDVI of bush and mash decreased, and the downward trend was significant for bush. The NDVI of the other seven vegetation types increased, and the upward trend was significant for coniferous forest, meadow, and alpine vegetation, and extremely significant for shrub. The mean annual temperature in the areas with all the nine vegetation types increased significantly, while the annual precipitation had no significant change. The drought index in the areas with marsh, bush, and cultural vegetation presented an increasing trend, that in the areas with meadow and alpine vegetation decreased significantly, and this index in the areas with other four vegetation types had an unobvious decreasing trend. The NDVI of shrub and coniferous forest had a significantly positive correlation with mean annual temperature, and that of shrub and meadow had significantly negative correlation with drought index. Under the conditions of the other two climatic factors unchanged, the NDVI of coniferous forest, broad-leaved forest, and alpine vegetation showed the strongest correlation with mean annual temperature, that of grass showed the strongest correlation with annual precipitation, and the NDVI of mash, shrub, grass, meadow, and cultural vegetation showed the strongest correlation with drought index. There existed definite correlations among the climatic factors. If the correlations among the climatic factors were ignored, the significant level of the correlations between NDVI and climatic factors would be somewhat reduced.

Modeling seasonal changes in live fuel moisture and equivalent water thickness using a cumulative water balance index

Treesearch

Philip E. Dennison; Dar A. Roberts; Sommer R. Thorgusen; Jon C. Regelbrugge; David Weise; Christopher Lee

2003-01-01

Live fuel moisture, an important determinant of fire danger in Mediterranean ecosystems, exhibits seasonal changes in response to soil water availability. Both drought stress indices based on meteorological data and remote sensing indices based on vegetation water absorption can be used to monitor live fuel moisture. In this study, a cumulative water balance index (...

Development of Forest Drought Index and Forest Water Use Prediction in Gyeonggi Province, Korea Using High-Resolution Weather Research and Forecast Data and Localized JULES Land Surface Model

NASA Astrophysics Data System (ADS)

Lee, H.; Park, J.; Cho, S.; Lee, S. J.; Kim, H. S.

2017-12-01

Forest determines the amount of water available to low land ecosystems, which use the rest of water after evapotranspiration by forests. Substantial increase of drought, especially for seasonal drought, has occurred in Korea due to climate change, recently. To cope with this increasing crisis, it is necessary to predict the water use of forest. In our study, forest water use in the Gyeonggi Province in Korea was estimated using high-resolution (spatial and temporal) meteorological forecast data and localized Joint UK Land Environment Simulator (JULES) which is one of the widely used land surface models. The modeled estimation was used for developing forest drought index. The localization of the model was conducted by 1) refining the existing two tree plant functional types (coniferous and deciduous trees) into five (Quercus spp., other deciduous tree spp., Pinus spp., Larix spp., and other coniferous spp.), 2) correcting moderate resolution imaging spectroradiometer (MODIS) leaf area index (LAI) through data assimilation with in situ measured LAI, and 3) optimizing the unmeasured plant physiological parameters (e.g. leaf nitrogen contents, nitrogen distribution within canopy, light use efficiency) based on sensitivity analysis of model output values. The high-resolution (hourly and 810 × 810 m) National Center for AgroMeteorology-Land-Atmosphere Modeling Package (NCAM-LAMP) data were employed as meteorological input data in JULES. The plant functional types and soil texture of each grid cell in the same resolution with that of NCAM-LAMP was also used. The performance of the localized model in estimating forest water use was verified by comparison with the multi-year sapflow measurements and Eddy covariance data of Taehwa Mountain site. Our result can be used as referential information to estimate the forest water use change by the climate change. Moreover, the drought index can be used to foresee the drought condition and prepare to it.

Spatial and Temporal Variation of Meteorological Drought in the Parambikulam-Aliyar Basin, Tamil Nadu

NASA Astrophysics Data System (ADS)

Manikandan, M.; Tamilmani, D.

2015-09-01

The present study aims to investigate the spatial and temporal variation of meteorological drought in the Parambikulam-Aliyar basin, Tamil Nadu using the Standardized Precipitation Index (SPI) as an indicator of drought severity. The basin was divided into 97 grid-cells of 5 × 5 km with each grid correspondence to approximately 1.03 % of total area. Monthly rainfall data for the period of 40 years (1972-2011) from 28 rain gauge stations in the basin was spatially interpolated and gridded monthly rainfall was created. Regional representative of SPI values calculated from mean areal rainfall were used to analyse the temporal variation of drought at multiple time scales. Spatial variation of drought was analysed based on highest drought severity derived from the monthly gridded SPI values. Frequency analyse was applied to assess the recurrence pattern of drought severity. The temporal analysis of SPI indicated that moderate, severe and extreme droughts are common in the basin and spatial analysis of drought severity identified the areas most frequently affected by drought. The results of this study can be used for developing drought preparedness plan and formulating mitigation strategies for sustainable water resource management within the basin.

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

PubMed

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

2016-07-01

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

Testing the use of standardised indices and GRACE satellite data to estimate the European 2015 groundwater drought in near-real time

NASA Astrophysics Data System (ADS)

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

2017-04-01

In 2015, central and eastern Europe were affected by a severe drought. This event has recently been studied from meteorological and streamflow perspective, but no analysis of the groundwater situation has been performed. One of the reasons is that real-time groundwater level observations often are not available. In this study, we evaluate two alternative approaches to quantify the 2015 groundwater drought over two regions in southern Germany and eastern Netherlands. The first approach is based on spatially explicit relationships between meteorological conditions and historic groundwater level observations. The second approach uses the Gravity Recovery Climate Experiment (GRACE) terrestrial water storage (TWS) and groundwater anomalies derived from GRACE-TWS and (near-)surface storage simulations by the Global Land Data Assimilation System (GLDAS) models. We combined the monthly groundwater observations from 2040 wells to establish the spatially varying optimal accumulation period between the Standardised Groundwater Index (SGI) and the Standardized Precipitation Evapotranspiration Index (SPEI) at a 0.25° gridded scale. The resulting optimal accumulation periods range between 1 and more than 24 months, indicating strong spatial differences in groundwater response time to meteorological input over the region. Based on the estimated optimal accumulation periods and available meteorological time series, we reconstructed the groundwater anomalies up to 2015 and found that in Germany a uniform severe groundwater drought persisted for several months during this year, whereas the Netherlands appeared to have relatively high groundwater levels. The differences between this event and the 2003 European benchmark drought are striking. The 2003 groundwater drought was less uniformly pronounced, both in the Netherlands and Germany. This is because slowly responding wells (the ones with optimal accumulation periods of more than 12 months) still were above average from the wet year of 2002, which experienced severe flooding in central Europe. GRACE-TWS and GRACE-based groundwater anomalies did not capture the spatial variability of the 2003 and 2015 drought events satisfactorily. GRACE-TWS did show that both 2003 and 2015 were relatively dry, but the differences between Germany and the Netherlands in 2015 and the spatially variable groundwater drought pattern in 2003 were not captured. This could be associated with the coarse spatial scale of GRACE. The simulated groundwater anomalies based on GRACE-TWS deviated considerably from the GRACE-TWS signal and from observed groundwater anomalies. The uncertainty in the GRACE-based groundwater anomalies mainly results from uncertainties in the simulation of soil moisture by the different GLDAS models. The GRACE-based groundwater anomalies are therefore not suitable for use in real-time groundwater drought monitoring in our case study regions. The alternative approach based on the spatially variable relationship between meteorological conditions and groundwater levels is more suitable to quantify groundwater drought in near real-time. Compared to the meteorological drought and streamflow drought (described in previous studies), the groundwater drought of 2015 had a more pronounced spatial variability in its response to meteorological conditions, with some areas primarily influenced by short-term meteorological deficits and others influenced by meteorological deficits accumulated over the preceding 2 years or more. In drought management, this information is very useful and our approach to quantify groundwater drought can be used until real-time groundwater observations become readily available.

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

NASA Astrophysics Data System (ADS)

Ruhoff, Anderson

2014-05-01

Evapotranspiration (ET), including water loss from plant transpiration and land evaporation, is of vital importance for understanding hydrological processes and climate dynamics and remote sensing is considered as the most important tool for estimate ET over large areas. The Moderate Resolution Imaging Spectroradiometer (MODIS) offers an interesting opportunity to evaluate ET with spatial resolution of 1 km. The MODIS global evapotranspiration algorithm (MOD16) considers both surface energy fluxes and climatic constraints on ET (water or temperature stress) to predict plant transpiration and soil evaporation based on Penman-Monteith equation. The algorithm is driven by remotely sensed and reanalysis meteorological data. In this study, MOD16 algorithm was applied to Southern Brazil to evaluate drought occurrences and its impacts over the agricultural production. Drought is a chronic potential natural disaster characterized by an extended period of time in which less water is available than expected, typically classified as meteorological, agricultural, hydrological and socioeconomic. With human-induced climate change, increases in the frequency, duration and severity of droughts are expected, leading to negative impacts in several sectors, such as agriculture, energy, transportation, urban water supply, among others. The current drought indicators are primarily based on precipitation, however only a few indicators incorporate ET and soil moisture components. ET and soil moisture play an important role in the assessment of drought severity as sensitive indicators of land drought status. To evaluate the drought occurrences in Southern Brazil from 2000 to 2012, we used the Evaporative Stress Index (ESI). The ESI, defined as 1 (one) minus the ratio of actual ET to potential ET, is one of the most important indices denoting ET and soil moisture responses to surface dryness with effects over natural ecosystems and agricultural areas. Results showed that ESI captured major regional droughts (2005, 2010 and 2012) occurred in Southern Brazil, with similar wetting and drying patterns based on the Standardized Precipitation Index (SPI) and strong correlation with agricultural productivity. Overall, the MODIS remotely sensed drought indices reveal the efficacy and effectiveness for near-real time monitor land surface drought events. Furthermore, understanding and predicting the consequences of drought events on agricultural productivity is emerging as one of the greatest challenges currently due to the increasing global demand for food. Acknowledgements: This work was made possible through the support of the Fundação de Amparo à Pesquisa do Estado do Rio Grande do Sul (FAPERGS).

Spatiotemporal variation of long-term drought propensity through reliability-resilience-vulnerability based Drought Management Index

NASA Astrophysics Data System (ADS)

Chanda, Kironmala; Maity, Rajib; Sharma, Ashish; Mehrotra, Rajeshwar

2014-10-01

This paper characterizes the long-term, spatiotemporal variation of drought propensity through a newly proposed, namely Drought Management Index (DMI), and explores its predictability in order to assess the future drought propensity and adapt drought management policies for a location. The DMI was developed using the reliability-resilience-vulnerability (RRV) rationale commonly used in water resources systems analysis, under the assumption that depletion of soil moisture across a vertical soil column is equivalent to the operation of a water supply reservoir, and that drought should be managed not simply using a measure of system reliability, but should also take into account the readiness of the system to bounce back from drought to a normal state. Considering India as a test bed, 5 year long monthly gridded (0.5° Lat × 0.5° Lon) soil moisture data are used to compute the RRV at each grid location falling within the study domain. The Permanent Wilting Point (PWP) is used as the threshold, indicative of transition into water stress. The association between resilience and vulnerability is then characterized through their joint probability distribution ascertained using Plackett copula models for four broad soil types across India. The joint cumulative distribution functions (CDF) of resilience and vulnerability form the basis for estimating the DMI as a five-yearly time series at each grid location assessed. The status of DMI over the past 50 years indicate that drought propensity is consistently low toward northern and north eastern parts of India but higher in the western part of peninsular India. Based on the observed past behavior of DMI series on a climatological time scale, a DMI prediction model comprising deterministic and stochastic components is developed. The predictability of DMI for a lead time of 5 years is found to vary across India, with a Pearson correlation coefficient between observed and predicted DMI above 0.6 over most of the study area, indicating a reasonably good potential for drought management in the medium term water resources planning horizon.

Comparison of satellite-derived LAI and precipitation anomalies over Brazil with a thermal infrared-based Evaporative Stress Index for 2003-2013

NASA Astrophysics Data System (ADS)

Anderson, Martha C.; Zolin, Cornelio A.; Hain, Christopher R.; Semmens, Kathryn; Tugrul Yilmaz, M.; Gao, Feng

2015-07-01

Shortwave vegetation index (VI) and leaf area index (LAI) remote sensing products yield inconsistent depictions of biophysical response to drought and pluvial events that have occurred in Brazil over the past decade. Conflicting reports of severity of drought impacts on vegetation health and functioning have been attributed to cloud and aerosol contamination of shortwave reflectance composites, particularly over the rainforested regions of the Amazon basin which are subject to prolonged periods of cloud cover and episodes of intense biomass burning. This study compares timeseries of satellite-derived maps of LAI from the Moderate Resolution Imaging Spectroradiometer (MODIS) and precipitation from the Tropical Rainfall Mapping Mission (TRMM) with a diagnostic Evaporative Stress Index (ESI) retrieved using thermal infrared remote sensing over South America for the period 2003-2013. This period includes several severe droughts and floods that occurred both over the Amazon and over unforested savanna and agricultural areas in Brazil. Cross-correlations between absolute values and standardized anomalies in monthly LAI and precipitation composites as well as the actual-to-reference evapotranspiration (ET) ratio used in the ESI were computed for representative forested and agricultural regions. The correlation analyses reveal strong apparent anticorrelation between MODIS LAI and TRMM precipitation anomalies over the Amazon, but better coupling over regions vegetated with shorter grass and crop canopies. The ESI was more consistently correlated with precipitation patterns over both landcover types. Temporal comparisons between ESI and TRMM anomalies suggest longer moisture buffering timescales in the deeper rooted rainforest systems. Diagnostic thermal-based retrievals of ET and ET anomalies, such as used in the ESI, provide independent information on the impacts of extreme hydrologic events on vegetation health in comparison with VI and precipitation-based drought indicators, and used in concert may provide a more reliable evaluation of natural and managed ecosystem response to variable climate regimes.

Projected climatic changes on drought conditions over Spain

NASA Astrophysics Data System (ADS)

García-Valdecasas Ojeda, Matilde; Quishpe-Vásquez, César; Raquel Gámiz-Fortis, Sonia; Castro-Díez, Yolanda; Jesús Esteban-Parra, María

2017-04-01

In a context of global warming, the evapotranspiration processes will have a strong influence on drought severity. For this reason, the Standardized Precipitation Evapotranspiration Index (SPEI) was computed at different timescales in order to explore the projected drought changes for the main watersheds in Spain. For that, the Weather Research and Forecasting (WRF) model has been used in order to obtain current (1980-2010) and future (2021-2050 and 2071-2100) climate output fields. WRF model was used over a domain that spans the Iberian Peninsula with a spatial resolution of 0.088°, and nested in the coarser 0.44° EURO-CORDEX domain, and driving by the global bias-corrected climate model output data from version 1 of NCAR's Community Earth System Model (CESM1), using two different Representative Concentration Pathway (RCP) scenarios: RCP 4.5 and RCP 8.5. Besides, to examine the behavior of this drought index, a comparison with the Standardized Precipitation Index (SPI), which does not consider the evapotranspiration effects, was also performed. Additionally the relationship between the SPEI index and the soil moisture has also been analyzed. The results of this study suggest an increase in the severity and duration of drought, being larger when the SPEI index is used to define drought events. This fact confirms the relevance of taking into account the evapotranspiration processes to detect future drought events. The results also show a noticeable relationship between the SPEI and the simulated soil moisture content, which is more significant at higher timescales. Keywords: Drought, SPEI, SPI, Climatic change, Projections, WRF. Acknowledgements: This work has been financed by the projects P11-RNM-7941 (Junta de Andalucía-Spain) and CGL2013-48539-R (MINECO-Spain, FEDER).

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Risk identification of agricultural drought for sustainable agroecosystems

NASA Astrophysics Data System (ADS)

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

2014-04-01

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

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

NASA Astrophysics Data System (ADS)

Mendicino, Giuseppe; Senatore, Alfonso; Versace, Pasquale

2008-08-01

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

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Application of Archimedean copulas to the analysis of drought decadal variation in China

NASA Astrophysics Data System (ADS)

Zuo, Dongdong; Feng, Guolin; Zhang, Zengping; Hou, Wei

2017-12-01

Based on daily precipitation data collected from 1171 stations in China during 1961-2015, the monthly standardized precipitation index was derived and used to extract two major drought characteristics which are drought duration and severity. Next, a bivariate joint model was established based on the marginal distributions of the two variables and Archimedean copula functions. The joint probability and return period were calculated to analyze the drought characteristics and decadal variation. According to the fit analysis, the Gumbel-Hougaard copula provided the best fit to the observed data. Based on four drought duration classifications and four severity classifications, the drought events were divided into 16 drought types according to the different combinations of duration and severity classifications, and the probability and return period were analyzed for different drought types. The results showed that the occurring probability of six common drought types (0 < D ≤ 1 and 0.5 < S ≤ 1, 1 < D ≤ 3 and 0.5 < S ≤ 1, 1 < D ≤ 3 and 1 < S ≤ 1.5, 1 < D ≤ 3 and 1.5 < S ≤ 2, 1 < D ≤ 3 and 2 < S, and 3 < D ≤ 6 and 2 < S) accounted for 76% of the total probability of all types. Moreover, due to their greater variation, two drought types were particularly notable, i.e., the drought types where D ≥ 6 and S ≥ 2. Analyzing the joint probability in different decades indicated that the location of the drought center had a distinctive stage feature, which cycled from north to northeast to southwest during 1961-2015. However, southwest, north, and northeast China had a higher drought risk. In addition, the drought situation in southwest China should be noted because the joint probability values, return period, and the analysis of trends in the drought duration and severity all indicated a considerable risk in recent years.

Spatial and decadal variations in satellite-based terrestrial evapotranspiration and drought over Inner Mongolia Autonomous Region of China during 1982-2009

NASA Astrophysics Data System (ADS)

Zhang, Zhaolu; Kang, Hui; Yao, Yunjun; Fadhil, Ayad M.; Zhang, Yuhu; Jia, Kun

2017-12-01

Evapotranspiration ( ET) plays an important role in exchange of water budget and carbon cycles over the Inner Mongolia autonomous region of China (IMARC). However, the spatial and decadal variations in terrestrial ET and drought over the IMARC in the past was calculated by only using sparse meteorological point-based data which remain quite uncertain. In this study, by combining satellite and meteorology datasets, a satellite-based semi-empirical Penman ET (SEMI-PM) algorithm is used to estimate regional ET and evaporative wet index (EWI) calculated by the ratio of ET and potential ET ( PET) over the IMARC. Validation result shows that the square of the correlation coefficients (R2) for the four sites varies from 0.45 to 0.84 and the root-mean-square error (RMSE) is 0.78 mm. We found that the ET has decreased on an average of 4.8 mm per decade (p=0.10) over the entire IMARC during 1982-2009 and the EWI has decreased on an average of 1.1% per decade (p=0.08) during the study period. Importantly, the patterns of monthly EWI anomalies have a good spatial and temporal correlation with the Palmer Drought Severity Index (PDSI) anomalies from 1982 to 2009, indicating EWI can be used to monitor regional surface drought with high spatial resolution. In high-latitude ecosystems of northeast region of the IMARC, both air temperature (Ta) and incident solar radiation (Rs) are the most important parameters in determining ET. However, in semiarid and arid areas of the central and southwest regions of the IMARC, both relative humidity (RH) and normalized difference vegetation index (NDVI) are the most important factors controlling annual variation of ET.

The impact exploration of agricultural drought on winter wheat yield in the North China Plain

NASA Astrophysics Data System (ADS)

Yang, Jianhua; Wu, Jianjun; Han, Xinyi; Zhou, Hongkui

2017-04-01

Drought is one of the most serious agro-climatic disasters in the North China Plain, which has a great influence on winter wheat yield. Global warming exacerbates the drought trend of this region, so it is important to study the effect of drought on winter wheat yield. In order to assess the drought-induced winter wheat yield losses, SPEI (standardized precipitation evapotranspiration index), the widely used drought index, was selected to quantify the drought from 1981 to 2013. Additionally, the EPIC (Environmental Policy Integrated Climate) crop model was used to simulate winter wheat yield at 47 stations in this region from 1981 to 2013. We analyzed the relationship between winter wheat yield and the SPEI at different time scales in each month during the growing season. The trends of the SPEI and the trends of winter wheat yield at 47 stations over the past 32 years were compared with each other. To further quantify the effect of drought on winter wheat yield, we defined the year that SPEI varied from -0.5 to 0.5 as the normal year, and calculated the average winter wheat yield of the normal years as a reference yield, then calculated the reduction ratios of winter wheat based on the yields mentioned above in severe drought years. As a reference, we compared the results with the reduction ratios calculated from the statistical yield data. The results showed that the 9 to 12-month scales' SPEI in April, May and June had a high correlation with winter wheat yield. The trends of the SPEI and the trends of winter wheat yield over the past 32 years showed a positive correlation (p<0.01) and have similar spatial distributions. The proportion of the stations with the same change trend between the SPEI and winter wheat yield was 70%, indicating that drought was the main factor leading to a decline in winter wheat yield in this region. The reduction ratios based on the simulated yield and the reduction ratios calculated from the statistical yield data have a high positive correlation (p<0.01), which may provide a way to quantitatively evaluate the winter wheat yield losses caused by drought. Key words: drought, winter wheat yield, SPEI, EPIC, the North China Plain

Evaluation of the Performance of Multiple Drought Indices for Tunisia

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Transition of the GOES Evapotranspiration and Drought Product System (GET-D) into Operations at NOAA/NESDIS

NASA Astrophysics Data System (ADS)

Hain, C.; Anderson, M. C.; Fang, L.; Zhan, X.; Otkin, J.

2016-12-01

Abnormally dry conditions can adversely affect the health of agricultural crops if the dryness persists for an extended period of time or if it occurs at a sensitive stage of crop development. Depending on its severity and timing, drought can result in significant yield loss, with impacts on both local and global markets as signified by reduced economic output and higher grain and food prices. Due to changing climate conditions, we are moving into a regime where processes controlling drought evolution are becoming more variable and are shifting in intensity, frequency and duration. The unusually rapid increase in water stress during some of these drought events are not well predicted by standard drought indicators. Different remote sensing indicators sample moisture and vegetation conditions occurring on different time scales during the typical evolution of agricultural drought. It has been shown that the thermal-based Evaporative Stress Index (ESI), based on land surface temperature, has an early warning component where vegetation stress manifested through decreased root-zone soil moisture leads to detectable vegetation stress in the LST signal before degradation in vegetation health is observed in VIS/NIR drought indices (e.g., NDVI). To provide this data to a larger user community and address the needs of our project stakeholders, the GOES Evapotranspiration and Drought Product System (GET-D) has been developed to operationally generate daily ET and ESI maps over the North America. The core model in GET-D is the Atmosphere-Land Exchange Inverse model (ALEXI), which is built on the two-source energy (TSEB) approach and partitions the GOES land surface temperature into characteristic soil and canopy temperatures, based on the fraction of vegetation cover. The primary operational data products of the GET-D system include the daily clear-sky ET and daily 2, 4, 8 and 12 week composites of the Evaporative Stress Index (ESI) computed from the ET daily estimates over North America at a spatial resolution of 8 km. This talk will focus on the evaluation of the operational data products, lessons learned from the transition into operations and the planned global expansion of the GET-D system at NOAA.

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

NASA Astrophysics Data System (ADS)

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

2012-12-01

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

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.

Drought prediction using co-active neuro-fuzzy inference system, validation, and uncertainty analysis (case study: Birjand, Iran)

NASA Astrophysics Data System (ADS)

Memarian, Hadi; Pourreza Bilondi, Mohsen; Rezaei, Majid

2016-08-01

This work aims to assess the capability of co-active neuro-fuzzy inference system (CANFIS) for drought forecasting of Birjand, Iran through the combination of global climatic signals with rainfall and lagged values of Standardized Precipitation Index (SPI) index. Using stepwise regression and correlation analyses, the signals NINO 1 + 2, NINO 3, Multivariate Enso Index, Tropical Southern Atlantic index, Atlantic Multi-decadal Oscillation index, and NINO 3.4 were recognized as the effective signals on the drought event in Birjand. Based on the results from stepwise regression analysis and regarding the processor limitations, eight models were extracted for further processing by CANFIS. The metrics P-factor and D-factor were utilized for uncertainty analysis, based on the sequential uncertainty fitting algorithm. Sensitivity analysis showed that for all models, NINO indices and rainfall variable had the largest impact on network performance. In model 4 (as the model with the lowest error during training and testing processes), NINO 1 + 2(t-5) with an average sensitivity of 0.7 showed the highest impact on network performance. Next, the variables rainfall, NINO 1 + 2(t), and NINO 3(t-6) with the average sensitivity of 0.59, 0.28, and 0.28, respectively, could have the highest effect on network performance. The findings based on network performance metrics indicated that the global indices with a time lag represented a better correlation with El Niño Southern Oscillation (ENSO). Uncertainty analysis of the model 4 demonstrated that 68 % of the observed data were bracketed by the 95PPU and D-Factor value (0.79) was also within a reasonable range. Therefore, the fourth model with a combination of the input variables NINO 1 + 2 (with 5 months of lag and without any lag), monthly rainfall, and NINO 3 (with 6 months of lag) and correlation coefficient of 0.903 (between observed and simulated SPI) was selected as the most accurate model for drought forecasting using CANFIS in the climatic region of Birjand.

Drought variability in the eastern Australia and New Zealand summer drought atlas (ANZDA, CE 1500-2012) modulated by the Interdecadal Pacific Oscillation

NASA Astrophysics Data System (ADS)

Palmer, Jonathan G.; Cook, Edward R.; Turney, Chris S. M.; Allen, Kathy; Fenwick, Pavla; Cook, Benjamin I.; O'Donnell, Alison; Lough, Janice; Grierson, Pauline; Baker, Patrick

2015-12-01

Agricultural production across eastern Australia and New Zealand is highly vulnerable to drought, but there is a dearth of observational drought information prior to CE 1850. Using a comprehensive network of 176 drought-sensitive tree-ring chronologies and one coral series, we report the first Southern Hemisphere gridded drought atlas extending back to CE 1500. The austral summer (December-February) Palmer drought sensitivity index reconstruction accurately reproduces historically documented drought events associated with the first European settlement of Australia in CE 1788, and the leading principal component explains over 50% of the underlying variance. This leading mode of variability is strongly related to the Interdecadal Pacific Oscillation tripole index (IPO), with a strong and robust antiphase correlation between (1) eastern Australia and the New Zealand North Island and (2) the South Island. Reported positive, negative, and neutral phases of the IPO are consistently reconstructed by the drought atlas although the relationship since CE 1976 appears to have weakened.

Drought Variability in the Eastern Australia and New Zealand Summer Drought Atlas (ANZDA, CE 1500-2012) Modulated by the Interdecadal Pacific Oscillation

NASA Technical Reports Server (NTRS)

Palmer, Jonathan G.; Cook, Edward R.; Turney, Chris S. M.; Allen, Kathy; Fenwick, Pavla; Cook, Benjamin I.; O'Donnell, Alison; Lough, Janice; Grierson, Pauline; Baker, Patrick

2015-01-01

Agricultural production across eastern Australia and New Zealand is highly vulnerable to drought, but there is a dearth of observational drought information prior to CE (Christian Era) 1850. Using a comprehensive network of 176 drought-sensitive tree-ring chronologies and one coral series, we report the first Southern Hemisphere gridded drought atlas extending back to CE 1500. The austral summer (December-February) Palmer drought sensitivity index reconstruction accurately reproduces historically documented drought events associated with the first European settlement of Australia in CE 1788, and the leading principal component explains over 50 percent of the underlying variance. This leading mode of variability is strongly related to the Interdecadal Pacific Oscillation tripole index (IPO), with a strong and robust antiphase correlation between (1) eastern Australia and the New Zealand North Island and (2) the South Island. Reported positive, negative, and neutral phases of the IPO are consistently reconstructed by the drought atlas although the relationship since CE 1976 appears to have weakened.

Exploring the Components of the Palmer Drought Indices Using the Apalachicola-Chattahoochee-Flint (ACF) River Basin as a Case Study

NASA Astrophysics Data System (ADS)

Perrone, D.; Duncan, L. L.; Jacobi, J. H.; Hornberger, G.

2012-12-01

Water resources are vital to sustaining ecosystem services, energy and food supplies, and industrial processes. Competition for water resources is likely to intensify as the population increases, economy grows, and land develops. Drought events intensify water scarcity, and recent events in many countries, including the United States (US), Great Britain, and Sri Lanka, highlight how important it is to provide meaningful context to water planners and managers. Palmer's drought indices - Z Index, Palmer Drought Severity Index (PDSI), and Palmer Hydrological Drought Index (PHDI) - are widely used and accepted by scientists and policy makers in the US to understand drought and manage water resources. Drought index values at the climate division scale are available, but a transparent calculation tool at multiple spatial and temporal scales is not readily available. Moreover, a close look at the development of the indices reveals a number of subjective calculation methods and regionally biased factors. For researchers studying areas with overlapping climate divisions, performing international research, or working with limited, site-specific data, the ability to control and modify calculations is desired. This research presents a transparent tool for calculating Palmer's drought indices. We use the Apalachicola-Chattahoochee-Flint (ACF) River Basin, located in the southeastern US, as our case study to explore and evaluate the sensitivity of Palmer's indices to temperature and precipitation anomalies, calibration periods, and other index components. The ACF has suffered two major droughts (2007 and 2012) in the past five years and supports multiple demand-side sectors - agriculture in Georgia, public and recreational supply for the Atlanta metropolitan area, hydroelectric power in Alabama, tri-state navigation, and ecosystem services. We show how the PDSI varies in response to changes in precipitation, calibration period, and a number of other variables. The aim of the work is to make this easily used tool available to help professionals who work toward facilitating water management and reducing water conflicts in the future.

Drought trends based on the VCI and its correlation with climate factors in the agricultural areas of China from 1982 to 2010.

PubMed

Qian, Xiaojin; Liang, Liang; Shen, Qiu; Sun, Qin; Zhang, Lianpeng; Liu, Zhixiao; Zhao, Shuhe; Qin, Zhihao

2016-11-01

Drought is a type of natural disaster that has the most significant impacts on agriculture. Regional drought monitoring based on remote sensing has become popular due to the development of remote sensing technology. In this study, vegetation condition index (VCI) data recorded from 1982 to 2010 in agricultural areas of China were obtained from advanced very high resolution radiometer (AVHRR) data, and the temporal and spatial variations in each drought were analyzed. The relationships between drought and climate factors were also analyzed. The results showed that from 1982 to 2010, the agricultural areas that experienced frequent and severe droughts were mainly concentrated in the northwestern areas and Huang-Huai Plain. Moreover, the VCI increased in the majority of agricultural areas, indicating that the drought frequency decreased over time, and the decreasing trend in the southern region was more notable than that in the northern region. A correlation analysis showed that temperature and wind velocity were the main factors that influenced drought in the agricultural areas of China. From a regional perspective, excluding precipitation, the climate factors had various effects on drought in different regions. However, the correlation between the VCI and precipitation was low, possibly due to the widespread use of artificial irrigation technology, which reduces the reliance of agricultural areas on precipitation.

Enhancing Access to Drought Information Using the CUAHSI Hydrologic Information System

NASA Astrophysics Data System (ADS)

Schreuders, K. A.; Tarboton, D. G.; Horsburgh, J. S.; Sen Gupta, A.; Reeder, S.

2011-12-01

The National Drought Information System (NIDIS) Upper Colorado River Basin pilot study is investigating and establishing capabilities for better dissemination of drought information for early warning and management. As part of this study we are using and extending functionality from the Consortium of Universities for the Advancement of Hydrologic Science, Inc. (CUAHSI) Hydrologic Information System (HIS) to provide better access to drought-related data in the Upper Colorado River Basin. The CUAHSI HIS is a federated system for sharing hydrologic data. It is comprised of multiple data servers, referred to as HydroServers, that publish data in a standard XML format called Water Markup Language (WaterML), using web services referred to as WaterOneFlow web services. HydroServers can also publish geospatial data using Open Geospatial Consortium (OGC) web map, feature and coverage services and are capable of hosting web and map applications that combine geospatial datasets with observational data served via web services. HIS also includes a centralized metadata catalog that indexes data from registered HydroServers and a data access client referred to as HydroDesktop. For NIDIS, we have established a HydroServer to publish drought index values as well as the input data used in drought index calculations. Primary input data required for drought index calculation include streamflow, precipitation, reservoir storages, snow water equivalent, and soil moisture. We have developed procedures to redistribute the input data to the time and space scales chosen for drought index calculation, namely half monthly time intervals for HUC 10 subwatersheds. The spatial redistribution approaches used for each input parameter are dependent on the spatial linkages for that parameter, i.e., the redistribution procedure for streamflow is dependent on the upstream/downstream connectivity of the stream network, and the precipitation redistribution procedure is dependent on elevation to account for orographic effects. A set of drought indices are then calculated from the redistributed data. We have created automated data and metadata harvesters that periodically scan and harvest new data from each of the input databases, and calculates extensions to the resulting derived data sets, ensuring that the data available on the drought server is kept up to date. This paper will describe this system, showing how it facilitates the integration of data from multiple sources to inform the planning and management of water resources during drought. The system may be accessed at http://drought.usu.edu.

A copula-based assessment of Bartlett-Lewis type of rainfall models for preserving drought statistics

NASA Astrophysics Data System (ADS)

Pham, M. T.; Vanhaute, W. J.; Vandenberghe, S.; De Baets, B.; Verhoest, N. E. C.

2013-06-01

Of all natural disasters, the economic and environmental consequences of droughts are among the highest because of their longevity and widespread spatial extent. Because of their extreme behaviour, studying droughts generally requires long time series of historical climate data. Rainfall is a very important variable for calculating drought statistics, for quantifying historical droughts or for assessing the impact on other hydrological (e.g. water stage in rivers) or agricultural (e.g. irrigation requirements) variables. Unfortunately, time series of historical observations are often too short for such assessments. To circumvent this, one may rely on the synthetic rainfall time series from stochastic point process rainfall models, such as Bartlett-Lewis models. The present study investigates whether drought statistics are preserved when simulating rainfall with Bartlett-Lewis models. Therefore, a 105 yr 10 min rainfall time series obtained at Uccle, Belgium is used as test case. First, drought events were identified on the basis of the Effective Drought Index (EDI), and each event was characterized by two variables, i.e. drought duration (D) and drought severity (S). As both parameters are interdependent, a multivariate distribution function, which makes use of a copula, was fitted. Based on the copula, four types of drought return periods are calculated for observed as well as simulated droughts and are used to evaluate the ability of the rainfall models to simulate drought events with the appropriate characteristics. Overall, all Bartlett-Lewis type of models studied fail in preserving extreme drought statistics, which is attributed to the model structure and to the model stationarity caused by maintaining the same parameter set during the whole simulation period.

Probabilistic modelling of drought events in China via 2-dimensional joint copula

NASA Astrophysics Data System (ADS)

Ayantobo, Olusola O.; Li, Yi; Song, Songbai; Javed, Tehseen; Yao, Ning

2018-04-01

Probabilistic modelling of drought events is a significant aspect of water resources management and planning. In this study, popularly applied and several relatively new bivariate Archimedean copulas were employed to derive regional and spatial based copula models to appraise drought risk in mainland China over 1961-2013. Drought duration (Dd), severity (Ds), and peak (Dp), as indicated by Standardized Precipitation Evapotranspiration Index (SPEI), were extracted according to the run theory and fitted with suitable marginal distributions. The maximum likelihood estimation (MLE) and curve fitting method (CFM) were used to estimate the copula parameters of nineteen bivariate Archimedean copulas. Drought probabilities and return periods were analysed based on appropriate bivariate copula in sub-region I-VII and entire mainland China. The goodness-of-fit tests as indicated by the CFM showed that copula NN19 in sub-regions III, IV, V, VI and mainland China, NN20 in sub-region I and NN13 in sub-region VII are the best for modeling drought variables. Bivariate drought probability across mainland China is relatively high, and the highest drought probabilities are found mainly in the Northwestern and Southwestern China. Besides, the result also showed that different sub-regions might suffer varying drought risks. The drought risks as observed in Sub-region III, VI and VII, are significantly greater than other sub-regions. Higher probability of droughts of longer durations in the sub-regions also corresponds to shorter return periods with greater drought severity. These results may imply tremendous challenges for the water resources management in different sub-regions, particularly the Northwestern and Southwestern China.

Conceptual framework for drought phenotyping during molecular breeding.

PubMed

Salekdeh, Ghasem Hosseini; Reynolds, Matthew; Bennett, John; Boyer, John

2009-09-01

Drought is a major threat to agricultural production and drought tolerance is a prime target for molecular approaches to crop improvement. To achieve meaningful results, these approaches must be linked with suitable phenotyping protocols at all stages, such as the screening of germplasm collections, mutant libraries, mapping populations, transgenic lines and breeding materials and the design of OMICS and quantitative trait loci (QTLs) experiments. Here we present a conceptual framework for molecular breeding for drought tolerance based on the Passioura equation of expressing yield as the product of water use (WU), water use efficiency (WUE) and harvest index (HI). We identify phenotyping protocols that address each of these factors, describe their key features and illustrate their integration with different molecular approaches.

Siberian Pine Decline and Mortality in Southern Siberian Mountains

NASA Technical Reports Server (NTRS)

Kharuk, V. I.; Im, S. T.; Oskorbin, P. A.; Petrov, I. A.; Ranson, K. J.

2013-01-01

The causes and resulting spatial patterns of Siberian pine mortality in eastern Kuznetzky Alatau Mountains, Siberia were analyzed based on satellite (Landsat, MODIS) and dendrochronology data. Climate variables studied included temperature, precipitation and Standardized Precipitation-Evapotranspiration Index (SPEI) drought index. Landsat data analysis showed that stand mortality was first detected in the year 2006 at an elevation of 650 m, and extended up to 900 m by the year 2012. Mortality was accompanied by a decrease in MODIS derived vegetation index (EVI).. The area of dead stands and the upper mortality line were correlated with increased drought. The uphill margin of mortality was limited by elevational precipitation gradients. Dead stands (i.e., >75% tree mortality) were located mainly on southern slopes. With respect to slope, mortality was observed within a 7 deg - 20 deg range with greatest mortality occurring on convex terrain. Tree radial incrementmeasurements correlate and were synchronous with SPEI (r sq = 0.37, r(sub s) = 80). Increasing synchrony between tree ring growth and SPEI indicates that drought has reduced the ecological niche of Siberian pine. The results also showed the primary role of drought stress on Siberian pine mortality. A secondary role may be played by bark beetles and root fungi attacks. The observed Siberian pine mortality is part of a broader phenomenon of "dark needle conifers" (DNC, i.e., Siberian pine, fir and spruce) decline and mortality in European Russia, Siberia, and the Russian Far East. All locations of DNC decline coincided with areas of observed drought increase. The results obtained are one of the first observations of drought-induced decline and mortality of DNC at the southern border of boreal forests. Meanwhile if model projections of increased aridity are correct DNC, within the southern part of its range may be replaced by drought-resistant Pinus silvestris and Larix sibirica.

Application of the Artificial Neural Network model for prediction of monthly Standardized Precipitation and Evapotranspiration Index using hydrometeorological parameters and climate indices in eastern Australia

NASA Astrophysics Data System (ADS)

Deo, Ravinesh C.; Şahin, Mehmet

2015-07-01

The forecasting of drought based on cumulative influence of rainfall, temperature and evaporation is greatly beneficial for mitigating adverse consequences on water-sensitive sectors such as agriculture, ecosystems, wildlife, tourism, recreation, crop health and hydrologic engineering. Predictive models of drought indices help in assessing water scarcity situations, drought identification and severity characterization. In this paper, we tested the feasibility of the Artificial Neural Network (ANN) as a data-driven model for predicting the monthly Standardized Precipitation and Evapotranspiration Index (SPEI) for eight candidate stations in eastern Australia using predictive variable data from 1915 to 2005 (training) and simulated data for the period 2006-2012. The predictive variables were: monthly rainfall totals, mean temperature, minimum temperature, maximum temperature and evapotranspiration, which were supplemented by large-scale climate indices (Southern Oscillation Index, Pacific Decadal Oscillation, Southern Annular Mode and Indian Ocean Dipole) and the Sea Surface Temperatures (Nino 3.0, 3.4 and 4.0). A total of 30 ANN models were developed with 3-layer ANN networks. To determine the best combination of learning algorithms, hidden transfer and output functions of the optimum model, the Levenberg-Marquardt and Broyden-Fletcher-Goldfarb-Shanno (BFGS) quasi-Newton backpropagation algorithms were utilized to train the network, tangent and logarithmic sigmoid equations used as the activation functions and the linear, logarithmic and tangent sigmoid equations used as the output function. The best ANN architecture had 18 input neurons, 43 hidden neurons and 1 output neuron, trained using the Levenberg-Marquardt learning algorithm using tangent sigmoid equation as the activation and output functions. An evaluation of the model performance based on statistical rules yielded time-averaged Coefficient of Determination, Root Mean Squared Error and the Mean Absolute Error ranging from 0.9945-0.9990, 0.0466-0.1117, and 0.0013-0.0130, respectively for individual stations. Also, the Willmott's Index of Agreement and the Nash-Sutcliffe Coefficient of Efficiency were between 0.932-0.959 and 0.977-0.998, respectively. When checked for the severity (S), duration (D) and peak intensity (I) of drought events determined from the simulated and observed SPEI, differences in drought parameters ranged from - 1.41-0.64%, - 2.17-1.92% and - 3.21-1.21%, respectively. Based on performance evaluation measures, we aver that the Artificial Neural Network model is a useful data-driven tool for forecasting monthly SPEI and its drought-related properties in the region of study.

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

PubMed

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

2017-11-23

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

Modeling Drought Impact Occurrence Based on Climatological Drought Indices for Europe

NASA Astrophysics Data System (ADS)

Stagge, J. H.; Kohn, I.; Tallaksen, L. M.; Stahl, K.

2014-12-01

Meteorological drought indices are often assumed to accurately characterize the severity of a drought event; however, these indices do not necessarily reflect the likelihood or severity of a particular type of drought impact experienced on the ground. In previous research, this link between index and impact was often estimated based on thresholds found by experience, measured using composite indices with assumed weighting schemes, or defined based on very narrow impact measures, using either a narrow spatial extent or very specific impacts. This study expands on earlier work by demonstrating the feasibility of relating user-provided impact reports to the climatological drought indices SPI and SPEI by logistic regression. The user-provided drought impact reports are based on the European Drought Impact Inventory (EDII, www.geo.uio.no/edc/droughtdb/), a newly developed online database that allows both public report submission and querying the more than 4,000 reported impacts spanning 33 European countries. This new tool is used to quantify the link between meteorological drought indices and impacts focusing on four primary impact types, spanning agriculture, energy and industry, public water supply, and freshwater ecosystem across five European countries. Statistically significant climate indices are retained as predictors using step-wise regression and used to compare the most relevant drought indices and accumulation periods for different impact types and regions. Agricultural impacts are explained best by 2-12 month anomalies, with 2-3 month anomalies found in predominantly rain-fed agricultural regions, and anomalies greater than 3 months related to agricultural management practices. Energy and industry impacts, related to hydropower and energy cooling water in these countries, respond to longer accumulated precipitation anomalies (6-12 months). Public water supply and freshwater ecosystem impacts are explained by a more complex combination of short (1-3 month) and seasonal (6-12 month) anomalies. A mean of 47.0% (22.4-71.6%) impact deviance is explained by the resulting models, highlighting the feasibility of using such statistical techniques and drought impact databases to model drought impact likelihood based on relatively easily calculated meteorological drought indices.

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

NASA Astrophysics Data System (ADS)

Procházková, Petra; Chuchma, Filip; Středa, Tomáš

2016-12-01

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

Groundwater potential for water supply during droughts in Korea

NASA Astrophysics Data System (ADS)

Hyun, Y.; Cha, E.; Moon, H. J.

2016-12-01

Droughts have been receiving much attention in Korea because severe droughts occurred in recent years, causing significant social, economic and environmental damages in some regions. Residents in agricultural area, most of all, were most damaged by droughts with lack of available water supplies to meet crop water demands. In order to mitigate drought damages, we present a strategy to keep from agricultural droughts by using groundwater to meet water supply as a potential water resource in agricultural areas. In this study, we analyze drought severity and the groundwater potential to mitigate social and environmental damages caused by droughts in Korea. We evaluate drought severity by analyzing spatial and temporal meteorological and hydrological data such as rainfall, water supply and demand. For drought severity, we use effective drought index along with the standardized precipitation index (SPI) and standardized runoff index(SRI). Water deficit during the drought period is also quantified to consider social and environmental impact of droughts. Then we assess the feasibility of using groundwater as a potential source for groundwater impact mitigation. Results show that the agricultural areas are more vulnerable to droughts and use of groundwater as an emergency water resource is feasible in some regions. For a case study, we select Jeong-Sun area located in Kangwon providence having well-developed Karst aquifers and surrounded by mountains. For Jeong-Sun area, we quantify groundwater potential use, design the method of water supply by using groundwater, and assess its economic benefit. Results show that water supply system with groundwater abstraction can be a good strategy when droughts are severe for an emergency water supply in Jeong-Sun area, and groundwater can also be used not only for a dry season water supply resource, but for everyday water supply system. This case study results can further be applicable to some regions with no sufficient water infrastructure and high groundwater use potential. For concrete conclusions, rigorous study on performance evaluation of water supply using groundwater is further needed.

Soil salinity mapping and hydrological drought indices assessment in arid environments based on remote sensing techniques

NASA Astrophysics Data System (ADS)

Elhag, Mohamed; Bahrawi, Jarbou A.

2017-03-01

Vegetation indices are mostly described as crop water derivatives. The normalized difference vegetation index (NDVI) is one of the oldest remote sensing applications that is widely used to evaluate crop vigor directly and crop water relationships indirectly. Recently, several NDVI derivatives were exclusively used to assess crop water relationships. Four hydrological drought indices are examined in the current research study. The water supply vegetation index (WSVI), the soil-adjusted vegetation index (SAVI), the moisture stress index (MSI) and the normalized difference infrared index (NDII) are implemented in the current study as an indirect tool to map the effect of different soil salinity levels on crop water stress in arid environments. In arid environments, such as Saudi Arabia, water resources are under pressure, especially groundwater levels. Groundwater wells are rapidly depleted due to the heavy abstraction of the reserved water. Heavy abstractions of groundwater, which exceed crop water requirements in most of the cases, are powered by high evaporation rates in the designated study area because of the long days of extremely hot summer. Landsat 8 OLI data were extensively used in the current research to obtain several vegetation indices in response to soil salinity in Wadi ad-Dawasir. Principal component analyses (PCA) and artificial neural network (ANN) analyses are complementary tools used to understand the regression pattern of the hydrological drought indices in the designated study area.

Socioeconomic Drought in a Changing Climate: Modeling and Management

NASA Astrophysics Data System (ADS)

AghaKouchak, Amir; Mehran, Ali; Mazdiyasni, Omid

2016-04-01

Drought is typically defined based on meteorological, hydrological and land surface conditions. However, in many parts of the world, anthropogenic changes and water management practices have significantly altered local water availability. Socioeconomic drought refers to conditions whereby the available water supply cannot satisfy the human and environmental water needs. Surface water reservoirs provide resilience against local climate variability (e.g., droughts), and play a major role in regional water management. This presentation focuses on a framework for describing socioeconomic drought based on both water supply and demand information. We present a multivariate approach as a measure of socioeconomic drought, termed Multivariate Standardized Reliability and Resilience Index (MSRRI; Mehran et al., 2015). This model links the information on inflow and surface reservoir storage to water demand. MSRRI integrates a "top-down" and a "bottom-up" approach for describing socioeconomic drought. The "top-down" component describes processes that cannot be simply controlled or altered by local decision-makers and managers (e.g., precipitation, climate variability, climate change), whereas the "bottom-up" component focuses on the local resilience, and societal capacity to respond to droughts. The two components (termed, Inflow-Demand Reliability (IDR) indicator and Water Storage Resilience (WSR) indicator) are integrated using a nonparametric multivariate approach. We use this framework to assess the socioeconomic drought during the Australian Millennium Drought (1998-2010) and the 2011-2014 California Droughts. MSRRI provides additional information on socioeconomic drought onset, development and termination based on local resilience and human demand that cannot be obtained from the commonly used drought indicators. We show that MSRRI can be used for water management scenario analysis (e.g., local water availability based on different human water demands scenarios). Finally, we provide examples of using the proposed modeling framework for analyzing water availability in a changing climate considering local conditions. Reference: Mehran A., Mazdiyasni O., AghaKouchak A., 2015, A Hybrid Framework for Assessing Socioeconomic Drought: Linking Climate Variability, Local Resilience, and Demand, Journal of Geophysical Research, 120 (15), 7520-7533, doi: 10.1002/2015JD023147

Tipping point of a conifer forest ecosystem under severe drought

NASA Astrophysics Data System (ADS)

Huang, Kaicheng; Yi, Chuixiang; Wu, Donghai; Zhou, Tao; Zhao, Xiang; Blanford, William J.; Wei, Suhua; Wu, Hao; Ling, Du; Li, Zheng

2015-02-01

Drought-induced tree mortality has recently received considerable attention. Questions have arisen over the necessary intensity and duration thresholds of droughts that are sufficient to trigger rapid forest declines. The values of such tipping points leading to forest declines due to drought are presently unknown. In this study, we have evaluated the potential relationship between the level of tree growth and concurrent drought conditions with data of the tree growth-related ring width index (RWI) of the two dominant conifer species (Pinus edulis and Pinus ponderosa) in the Southwestern United States (SWUS) and the meteorological drought-related standardized precipitation evapotranspiration index (SPEI). In this effort, we determined the binned averages of RWI and the 11 month SPEI within the month of July within each bin of 30 of RWI in the range of 0-3000. We found a significant correlation between the binned averages of RWI and SPEI at the regional-scale under dryer conditions. The tipping point of forest declines to drought is predicted by the regression model as SPEItp = -1.64 and RWItp = 0, that is, persistence of the water deficit (11 month) with intensity of -1.64 leading to negligible growth for the conifer species. When climate conditions are wetter, the correlation between the binned averages of RWI and SPEI is weaker which we believe is most likely due to soil water and atmospheric moisture levels no longer being the dominant factor limiting tree growth. We also illustrate a potential application of the derived tipping point (SPEItp = -1.64) through an examination of the 2002 extreme drought event in the SWUS conifer forest regions. Distinguished differences in remote-sensing based NDVI anomalies were found between the two regions partitioned by the derived tipping point.

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

NASA Astrophysics Data System (ADS)

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

2017-07-01

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

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.

Historical drought patterns over Canada and their teleconnections with large-scale climate signals

NASA Astrophysics Data System (ADS)

Asong, Zilefac Elvis; Wheater, Howard Simon; Bonsal, Barrie; Razavi, Saman; Kurkute, Sopan

2018-06-01

Drought is a recurring extreme climate event and among the most costly natural disasters in the world. This is particularly true over Canada, where drought is both a frequent and damaging phenomenon with impacts on regional water resources, agriculture, industry, aquatic ecosystems, and health. However, nationwide drought assessments are currently lacking and impacted by limited ground-based observations. This study provides a comprehensive analysis of historical droughts over the whole of Canada, including the role of large-scale teleconnections. Drought events are characterized by the Standardized Precipitation Evapotranspiration Index (SPEI) over various temporal scales (1, 3, 6, and 12 consecutive months, 6 months from April to September, and 12 months from October to September) applied to different gridded monthly data sets for the period 1950-2013. The Mann-Kendall test, rotated empirical orthogonal function, continuous wavelet transform, and wavelet coherence analyses are used, respectively, to investigate the trend, spatio-temporal patterns, periodicity, and teleconnectivity of drought events. Results indicate that southern (northern) parts of the country experienced significant trends towards drier (wetter) conditions although substantial variability exists. Two spatially well-defined regions with different temporal evolution of droughts were identified - the Canadian Prairies and northern central Canada. The analyses also revealed the presence of a dominant periodicity of between 8 and 32 months in the Prairie region and between 8 and 40 months in the northern central region. These cycles of low-frequency variability are found to be associated principally with the Pacific-North American (PNA) and Multivariate El Niño/Southern Oscillation Index (MEI) relative to other considered large-scale climate indices. This study is the first of its kind to identify dominant periodicities in drought variability over the whole of Canada in terms of when the drought events occur, their duration, and how often they occur.

a New Framework for Characterising Simulated Droughts for Future Climates

NASA Astrophysics Data System (ADS)

Sharma, A.; Rashid, M.; Johnson, F.

2017-12-01

Significant attention has been focussed on metrics for quantifying drought. Lesser attention has been given to the unsuitability of current metrics in quantifying drought in a changing climate due to the clear non-stationarity in potential and actual evapotranspiration well into the future (Asadi-Zarch et al, 2015). This talk presents a new basis for simulating drought designed specifically for use with climate model simulations. Given the known uncertainty of climate model rainfall simulations, along with their inability to represent low-frequency variability attributes, the approach here adopts a predictive model for drought using selected atmospheric indicators. This model is based on a wavelet decomposition of relevant atmospheric predictors to filter out less relevant frequencies and formulate a better characterisation of the drought metric chosen as response. Once ascertained using observed precipication and associated atmospheric variables, these can be formulated from GCM simulations using a multivariate bias correction tool (Mehrotra and Sharma, 2016) that accounts for low-frequency variability, and a regression tool that accounts for nonlinear dependence (Sharma and Mehrotra, 2014). Use of only the relevant frequencies, as well as the corrected representation of cross-variable dependence, allows greater accuracy in characterising observed drought, from GCM simulations. Using simulations from a range of GCMs across Australia, we show here that this new method offers considerable advantages in representing drought compared to traditionally followed alternatives that rely on modelled rainfall instead. Reference:Asadi Zarch, M. A., B. Sivakumar, and A. Sharma (2015), Droughts in a warming climate: A global assessment of Standardized precipitation index (SPI) and Reconnaissance drought index (RDI), Journal of Hydrology, 526, 183-195. Mehrotra, R., and A. Sharma (2016), A Multivariate Quantile-Matching Bias Correction Approach with Auto- and Cross-Dependence across Multiple Time Scales: Implications for Downscaling, Journal of Climate, 29(10), 3519-3539. Sharma, A., and R. Mehrotra (2014), An information theoretic alternative to model a natural system using observational information alone, Water Resources Research, 50, 650-660, doi:10.1002/2013WR013845.

Forest fire danger index based on modifying Nesterov Index, fuel, and anthropogenic activities using MODIS TERRA, AQUA and TRMM satellite datasets

NASA Astrophysics Data System (ADS)

Suresh Babu, K. V.; Roy, Arijit; Ramachandra Prasad, P.

2016-05-01

Forest fire has been regarded as one of the major causes of degradation of Himalayan forests in Uttarakhand. Forest fires occur annually in more than 50% of forests in Uttarakhand state, mostly due to anthropogenic activities and spreads due to moisture conditions and type of forest fuels. Empirical drought indices such as Keetch-Byram drought index, the Nesterov index, Modified Nesterov index, the Zhdanko index which belongs to the cumulative type and the Angstrom Index which belongs to the daily type have been used throughout the world to assess the potential fire danger. In this study, the forest fire danger index has been developed from slightly modified Nesterov index, fuel and anthropogenic activities. Datasets such as MODIS TERRA Land Surface Temperature and emissivity (MOD11A1), MODIS AQUA Atmospheric profile product (MYD07) have been used to determine the dew point temperature and land surface temperature. Precipitation coefficient has been computed from Tropical Rainfall measuring Mission (TRMM) product (3B42RT). Nesterov index has been slightly modified according to the Indian context and computed using land surface temperature, dew point temperature and precipitation coefficient. Fuel type danger index has been derived from forest type map of ISRO based on historical fire location information and disturbance danger index has been derived from disturbance map of ISRO. Finally, forest fire danger index has been developed from the above mentioned indices and MODIS Thermal anomaly product (MOD14) has been used for validating the forest fire danger index.

Decadal Drought and Wetness Reconstructed for Subtropical North America in the Mexican Drought Atlas

NASA Astrophysics Data System (ADS)

Burnette, D. J.; Stahle, D. W.; Cook, E. R.; Villanueva Diaz, J.; Griffin, D.; Cook, B.

2014-12-01

A new drought atlas has been developed for subtropical North America, including the entire Republic of Mexico. This Mexican Drought Atlas (MXDA) is based on 251 tree-ring chronologies, including 82 from Mexico and another 169 from the southern U.S. and western Guatemala. Point-by-point principal components regression was used to reconstruct the self-calibrating Palmer Drought Severity Index (PDSI) for June-August. Calibration and verification statistics were improved over what was previously possible with the North American Drought Atlas, which was based on fewer chronologies only in Mexico. The MXDA will be served on the web with analytical tools for composite, correlation, and congruence analyses. The new PDSI reconstructions provide a more detailed estimation of decadal moisture regimes over the past 2000 years, but are most robust after 1400 AD, when several chronologies are available across Mexico. Droughts previously identified in a subset of chronologies are confirmed and their spatial impact quantified in the new reconstructions. This includes the intense drought of the mid-15th Century described in Aztec legend, the 16th Century megadrought, and "El Año del Hambre", one of the worst famines in Mexican history. We also use the best replicated portion of the MXDA in the 18th and 19th Centuries to reconstruct moisture anomalies during key time periods of Mexican turmoil (e.g., the Mexican War of Independence).

Summer drought reconstruction in northeastern Spain inferred from a tree ring latewood network since 1734

NASA Astrophysics Data System (ADS)

Tejedor, E.; Saz, M. A.; Esper, J.; Cuadrat, J. M.; de Luis, M.

2017-08-01

Drought recurrence in the Mediterranean is regarded as a fundamental factor for socioeconomic development and the resilience of natural systems in context of global change. However, knowledge of past droughts has been hampered by the absence of high-resolution proxies. We present a drought reconstruction for the northeast of the Iberian Peninsula based on a new dendrochronology network considering the Standardized Evapotranspiration Precipitation Index (SPEI). A total of 774 latewood width series from 387 trees of P. sylvestris and P. uncinata was combined in an interregional chronology. The new chronology, calibrated against gridded climate data, reveals a robust relationship with the SPEI representing drought conditions of July and August. We developed a summer drought reconstruction for the period 1734-2013 representative for the northeastern and central Iberian Peninsula. We identified 16 extremely dry and 17 extremely wet summers and four decadal scale dry and wet periods, including 2003-2013 as the driest episode of the reconstruction.

Tree ring-based seven-century drought records for the Western Himalaya, India

NASA Astrophysics Data System (ADS)

Yadav, Ram R.

2013-05-01

The paucity of available instrumental climate records in cold and arid regions of the western Himalaya, India, hampers our understanding of the long-term variability of regional droughts, which seriously affect the agrarian economy of the region. Using ring width chronologies of Cedrus deodara and Pinus gerardiana together from a network of moisture-stressed sites, Palmer Drought Severity Index values for October-May back to 1310 A.D. were developed. The twentieth century features dominant decadal-scale pluvial phases (1981-1995, 1952-1968, and 1918-1934) as compared to the severe droughts in the early seventeenth century (1617-1640) as well as late fifteenth to early sixteenth (1491-1526) centuries. The drought anomalies are positively (negatively) associated with central Pacific (Indo-Pacific Warm Pool) sea surface temperature anomalies. However, non-stationarity in such relationships appears to be the major riddle in the predictability of long-term droughts much needed for the sustainable development of the ecologically sensitive region of the Himalayas.

Seasonal and interannual variability of climate and vegetation indices across the Amazon.

PubMed

Brando, Paulo M; Goetz, Scott J; Baccini, Alessandro; Nepstad, Daniel C; Beck, Pieter S A; Christman, Mary C

2010-08-17

Drought exerts a strong influence on tropical forest metabolism, carbon stocks, and ultimately the flux of carbon to the atmosphere. Satellite-based studies have suggested that Amazon forests green up during droughts because of increased sunlight, whereas field studies have reported increased tree mortality during severe droughts. In an effort to reconcile these apparently conflicting findings, we conducted an analysis of climate data, field measurements, and improved satellite-based measures of forest photosynthetic activity. Wet-season precipitation and plant-available water (PAW) decreased over the Amazon Basin from 1996-2005, and photosynthetically active radiation (PAR) and air dryness (expressed as vapor pressure deficit, VPD) increased from 2002-2005. Using improved enhanced vegetation index (EVI) measurements (2000-2008), we show that gross primary productivity (expressed as EVI) declined with VPD and PAW in regions of sparse canopy cover across a wide range of environments for each year of the study. In densely forested areas, no climatic variable adequately explained the Basin-wide interannual variability of EVI. Based on a site-specific study, we show that monthly EVI was relatively insensitive to leaf area index (LAI) but correlated positively with leaf flushing and PAR measured in the field. These findings suggest that production of new leaves, even when unaccompanied by associated changes in LAI, could play an important role in Basin-wide interannual EVI variability. Because EVI variability was greatest in regions of lower PAW, we hypothesize that drought could increase EVI by synchronizing leaf flushing via its effects on leaf bud development.

Middle-term metropolitan water availability index assessment based on synergistic potentials of multi-sensor data

NASA Astrophysics Data System (ADS)

Chang, Ni-Bin; Yang, Y. Jeffrey; Daranpob, Ammarin

2010-03-01

The impact of recent drought and water pollution episodes results in an acute need to project future water availability to assist water managers in water utility infrastructure management within many metropolitan regions. Separate drought and water quality indices previously developed might not be sufficient for the purpose of such an assessment. This paper describes the development of the "Metropolitan Water Availability Index (MWAI)" and its potential applications in assessing the middle-term water availability at the watershed scale in a fast growing metropolitan region - the Manatee County near Tampa Bay, Florida, U.S.A. The MWAI framework is based on a statistical approach that seeks to reflect the continuous spatial and temporal variations of both water quantity and quality using a simple numerical index. Such a trend analysis will surely result in the final MWAI values for regional water management systems within a specified range. By using remote sensing technologies and data processing techniques, continuous monitoring of spatial and temporal distributions of key water availability variables, such as evapotranspiration (ET) and precipitation, is made achievable. These remote sensing technologies can be ground-based (e.g., radar estimates of rainfall), or based on remote sensing data gathered by aircraft or satellites. Using a middle term historical record, the MWAI was applied to the Manatee County water supplies. The findings clearly indicate that only eight out of twelve months in 2008 had positive MWAI values during the year. Such numerical findings are consistent with the observational evidence of statewide drought events in 2006-2008, which implies the time delay between the ending of severe drought period and the recovery of water availability in MWAI. It is expected that this forward-looking novel water availability forecasting platform will help provide a linkage in methodology between strategic planning, master planning, and the plant operation and adaptations in response to the MWAI implications.

Risk identification of agricultural drought for sustainable Agroecosystems

NASA Astrophysics Data System (ADS)

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

2014-09-01

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

Drought Analysis for Kuwait Using Standardized Precipitation Index

PubMed Central

2014-01-01

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

Monitoring Drought along the Gulf of Mexico and the Southeastern Atlantic Ocean Using the Coastal Salinity Index

NASA Astrophysics Data System (ADS)

Conrads, P. A.; Rouen, L.; Lackstrom, K.; McCloskey, B.

2017-12-01

Coastal droughts have a different dynamic than upland droughts, which are typically characterized by agricultural, hydrologic, meteorological, and (or) socio-economic impacts. Drought uniquely affects coastal ecosystems due to changes in salinity conditions of estuarine creeks and rivers. The location of the freshwater-saltwater interface in surface-water bodies is an important factor in the ecological and socio-economic dynamics of coastal communities. The location of the interface determines the freshwater and saltwater aquatic communities, fisheries spawning habitat, and the freshwater availability for municipal and industrial water intakes. The severity of coastal drought may explain changes in Vibrio bacteria impacts on shellfish harvesting and occurrence of wound infection, fish kills, harmful algal blooms, hypoxia, and beach closures. To address the data and information gap for characterizing coastal drought, a coastal salinity index (CSI) was developed using salinity data. The CSI uses a computational approach similar to the Standardized Precipitation Index (SPI). The CSI is computed for unique time intervals (for example 1-, 6-, 12-, and 24-month) that can characterize the onset and recovery of short- and long-term drought. Evaluation of the CSI indicates that the index can be used for different estuary types (for example: brackish, oligohaline, or mesohaline), for regional comparison between estuaries, and as an index of wet conditions (high freshwater inflow) in addition to drought (saline) conditions. In 2017, three activities in 2017 will be presented that enhance the use and application of the CSI. One, a software package was developed for the consistent computation of the CSI that includes preprocessing of salinity data, filling missing data, computing the CSI, post-processing, and generating the supporting metadata. Two, the CSI has been computed at sites along the Gulf of Mexico (Texas to Florida) and the Southeastern Atlantic Ocean (Florida to North Carolina), and three, using telemetered salinity data, the real-time computation of the CSI has been prototyped and disseminated on the web.

Future Drought Projections over the Iberian Peninsula using Drought Indices

NASA Astrophysics Data System (ADS)

Garcia-Valdecasas Ojeda, M.; Yeste Donaire, P.; Góngora García, T. M.; Gámiz-Fortis, S. R.; Castro-Diez, Y.; Esteban-Parra, M. J.

2017-12-01

Currently, drought events are the cause of numerous annual economic losses. In a context of climate change, it is expected an increase in the severity and the frequency of drought occurrences, especially in areas such as the Mediterranean region. This study makes use of two drought indices in order to analyze the potential changes on future drought events and their effects at different time scales over a vulnerable region, the Iberian Peninsula. The indices selected were the Standardized Precipitation Evapotranspiration Index (SPEI), which takes into account the global warming through the temperature, and the Standardized Precipitation Index (SPI), based solely on precipitation data, at a spatial resolution of 0.088º ( 10 km). For their computation, current (1980-2014) and future (2021-2050 and 2071-2100) high resolution simulations were carried out using the Weather Research and Forecasting (WRF) model over a domain centered in the Iberian Peninsula, and nested in the 0.44 EUROCORDEX region. WRF simulations were driven by two different global bias-corrected climate models: the version 1 of NCAR's Community Earth System Model (CESM1) and the Max Planck Institute's Earth System Model (MPI-ESM-LR), and under two different Representative Concentration Pathway (RCP) scenarios: RCP 4.5 and RCP 8.5. Future projections were analyzed regarding to changes in mean, median and variance of drought indices with respect to the historical distribution, as well as changes in the frequency and duration of moderate and severe drought events. In general, results suggest an increase in frequency and severity of drought, especially for 2071-2100 period in the RCP 8.5 scenario. Results also shown an increase of drought phenomena more evident using the SPEI. Conclusions from this study could provide a valuable contribution to the understanding of how the increase of the temperature would affect the drought variability in the Mediterranean regions which is necessary for a suitable decision making.Keywords: Drought, SPEI, SPI, Climatic change, Regional projections, WRF.ACKNOWLEDGEMENTS: This work has been financed by the projects P11-RNM-7941 (Junta de Andalucía) and CGL2013-48539-R (MINECO-Spain, FEDER). This analysis was carried out in the ALHAMBRA computer infrastructure at the University of Granada.

Contribution of Temperature to Chilean Droughts Using Ensemble Climate Projections

NASA Astrophysics Data System (ADS)

Zambrano-Bigiarini, M.; Alfieri, L.; Naumann, G.; Garreaud, R. D.

2017-12-01

Precipitation deficit is traditionally considered as the main driver of drought events, however the evolution of drought conditions is also influenced by other variables such as temperature, wind speed and evapotranspiration. In view of global warming, the effect of rising temperatures may lead to increased socio-economic drought impacts, particularly in vulnerable developing countries. In this work, we used two drought indices to analyze the impacts of precipitation and temperature on the frequency, severity and duration of Chilean droughts (25°S-56°S) during the XXI century, using multi-model climate projections consistent with the high-end RCP 8.5 scenario. An ensemble of seven global CMIP5 simulations were used to drive the Earth System Model EC-EARTH3-HR v3.1 over the 1976-2100 period, in order to increase the spatial resolution from the original grid to 0.35°. The Standardized Precipitation Index (SPI) was used to describe the impact of precipitation on drought conditions, while the Standardized Precipitation-Evapotranspiration Index (SPEI) was used to assess the effect of temperature -throughout changes in potential evapotranspiration- on drought characteristics at different time scales. Drought indices along with duration, severity and frequency of drought events were computed for a 30-year baseline period (1976-2005) and then compared to three 30-year periods representing short, medium and long-term scenarios (2011-2040, 2041-2070 and 2071-2100). Indices obtained from climate simulations during the baseline period were compared against the corresponding values derived from ground observations. Results obtained with SPI-12 reveal a progressive decrease in precipitation in Chile, which is consistent through all climate models, though each of them shows a different spatial pattern. Simulations based on SPEI-12 show that the expected increase in evaporative demand (driven by the temperature increase) for the region is likely to exacerbate the severity and duration of drought events. Findings of this work are an important support for timely preparation of drought adaptation and mitigation plans to improve water management strategies and resilience during the XXI century.

Characterization of 2014 summer drought over Henan province using remotely sensed data

NASA Astrophysics Data System (ADS)

Lu, Jing; Jia, Li; Zhou, Jie

2015-12-01

An exceptional drought struck Henan province during the summer of 2014. It caused directly the financial loss reaching to hundreds of billion Yuan (RMB), and brought the adverse influence for people's life, agricultural production as well as the ecosystem. The study in this paper characterized the Henan 2014 summer drought event through analyzing the spatial distribution of drought severity using precipitation data from Tropical Rainfall Measuring Mission (TRMM) sensor and Normalized difference vegetation index (NDVI) and land surface temperature (LST) products from Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. The trend analysis of the annual precipitation from 2003 to 2014 showed that the region over Henan province is becoming dry. Especially in the east of Henan province, the decrease of precipitation is more obvious with the maximum change rate of ~48 mm/year. The rainfall in summer (from June to August) of 2014 was the largest negtive anomaly in contrast with the same period of historical years, which was 43% lower than the average of the past ten years. Drought severity derived from Standardized Precipitation Index (SPI) indicated that all areas of Henan province experienced drought in summer of 2014 with different severity levels. The extreme drought, accounting for about 22.7 % of Henan total area, mainly occurred in Luohe, Xuchang, and Pingdingshan regions, and partly in Nanyang, Zhengzhou, and Jiaozuo. This is consistent with the statistics from local municipalities. The Normalized Drought Index Anomaly (NDAI), calculated from MODIS NDVI and LST products, can capture the evolution of the Henan 2014 summer drought effectively. Drought severity classified by NDAI also agreed well with the result from the SPI.

Utilizing Multi-Ensemble of Downscaled CMIP5 GCMs to Investigate Trends and Spatial and Temporal Extent of Drought in Willamette Basin

NASA Astrophysics Data System (ADS)

Ahmadalipour, A.; Beal, B.; Moradkhani, H.

2015-12-01

Changing climate and potential future increases in global temperature are likely to have impacts on drought characteristics and hydrologic cylce. In this study, we analyze changes in temporal and spatial extent of meteorological and hydrological droughts in future, and their trends. Three statistically downscaled datasets from NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP), Multivariate Adaptive Constructed Analogs (MACA), and Bias Correction and Spatial Disagregation (BCSD-PSU) each consisting of 10 CMIP5 Global Climate Models (GCM) are utilized for RCP4.5 and RCP8.5 scenarios. Further, Precipitation Runoff Modeling System (PRMS) hydrologic model is used to simulate streamflow from GCM inputs and assess the hydrological drought characteristics. Standard Precipitation Index (SPI) and Streamflow Drought Index (SDI) are the two indexes used to investigate meteorological and hydrological drought, respectively. Study is done for Willamette Basin with a drainage area of 29,700 km2 accommodating more than 3 million inhabitants and 25 dams. We analyze our study for annual time scale as well as three future periods of near future (2010-2039), intermediate future (2040-2069), and far future (2070-2099). Large uncertainty is found from GCM predictions. Results reveal that meteorological drought events are expected to increase in near future. Severe to extreme drought with large areal coverage and several years of occurance is predicted around year 2030 with the likelihood of exceptional drought for both drought types. SPI is usually showing positive trends, while SDI indicates negative trends in most cases.

Fir Decline and Mortality in the Southern Siberian Mountains

NASA Technical Reports Server (NTRS)

Kharuk, Viacheslav I.; Im, Sergei T.; Petrov, Ilya A.; Dvinskaya, Mariya, L.; Fedotova, Elena V.; Ranson, Kenneth J.

2016-01-01

Increased dieback and mortality of dark needle conifer (DNC) stands (composed of fir (Abies sibirica),Siberian pine (Pinus sibirica) and spruce (Picea obovata))were documented in Russia during recent decades. Here we analyzed spatial and temporal patterns of fir decline and mortality in the southern Siberian Mountains based on satellite, in situ and dendrochronological data. The studied stands are located within the boundary between DNC taiga to the north and forest-steppe to the south. Fir decline and mortality were observed to originate where topographic features contributed to maximal water-stress risk, i.e., steep (1825),convex, south-facing slopes with a shallow well-drained root zone. Fir regeneration survived droughts and increased stem radial growth, while upper canopy trees died. Tree ring width(TRW) growth negatively correlated with vapor pressure deficit (VPD), drought index and occurrence of late frosts, and positively with soil water content. Previous year growth conditions (i.e., drought index, VPD, soil water anomalies)have a high impact on current TRW (r 0.600.74). Fir mortality was induced by increased water stress and severe droughts (as a primary factor) in synergy with bark-beetles and fungi attacks (as secondary factors). Dendrochronology data indicated that fir mortality is a periodic process. In a future climate with increased aridity and drought frequency, fir (and Siberian pine) may disappear from portions of its current range (primarily within the boundary with the forest steppe)and is likely to be replaced by drought-tolerant species such as Pinus sylvestris and Larix sibirica.

A comparative assessment of projected meteorological and hydrological droughts: Elucidating the role of temperature

NASA Astrophysics Data System (ADS)

Ahmadalipour, Ali; Moradkhani, Hamid; Demirel, Mehmet C.

2017-10-01

The changing climate and the associated future increases in temperature are expected to have impacts on drought characteristics and hydrologic cycle. This paper investigates the projected changes in spatiotemporal characteristics of droughts and their future attributes over the Willamette River Basin (WRB) in the Pacific Northwest U.S. The analysis is performed using two subsets of downscaled CMIP5 global climate models (GCMs) each consisting of 10 models from two future scenarios (RCP4.5 and RCP8.5) for 30 years of historical period (1970-1999) and 90 years of future projections (2010-2099). Hydrologic modeling is conducted using the Precipitation Runoff Modeling System (PRMS) as a robust distributed hydrologic model with lower computational cost compared to other models. Meteorological and hydrological droughts are studied using three drought indices (i.e. Standardized Precipitation Index, Standardized Precipitation Evapotranspiration Index, Standardized Streamflow Index). Results reveal that the intensity and duration of hydrological droughts are expected to increase over the WRB, albeit the annual precipitation is expected to increase. On the other hand, the intensity of meteorological droughts do not indicate an aggravation for most cases. We explore the changes of hydrometeolorogical variables over the basin in order to understand the causes for such differences and to discover the controlling factors of drought. Furthermore, the uncertainty of projections are quantified for model, scenario, and downscaling uncertainty.

Assessments of Drought Impacts on Vegetation in China with the Optimal Time Scales of the Climatic Drought Index.

PubMed

Li, Zheng; Zhou, Tao; Zhao, Xiang; Huang, Kaicheng; Gao, Shan; Wu, Hao; Luo, Hui

2015-07-08

Drought is expected to increase in frequency and severity due to global warming, and its impacts on vegetation are typically extensively evaluated with climatic drought indices, such as multi-scalar Standardized Precipitation Evapotranspiration Index (SPEI). We analyzed the covariation between the SPEIs of various time scales and the anomalies of the normalized difference vegetation index (NDVI), from which the vegetation type-related optimal time scales were retrieved. The results indicated that the optimal time scales of needle-leaved forest, broadleaf forest and shrubland were between 10 and 12 months, which were considerably longer than the grassland, meadow and cultivated vegetation ones (2 to 4 months). When the optimal vegetation type-related time scales were used, the SPEI could better reflect the vegetation's responses to water conditions, with the correlation coefficients between SPEIs and NDVI anomalies increased by 5.88% to 28.4%. We investigated the spatio-temporal characteristics of drought and quantified the different responses of vegetation growth to drought during the growing season (April-October). The results revealed that the frequency of drought has increased in the 21st century with the drying trend occurring in most of China. These results are useful for ecological assessments and adapting management steps to mitigate the impact of drought on vegetation. They are helpful to employ water resources more efficiently and reduce potential damage to human health caused by water shortages.

Effects of cold plasma treatment on alfalfa seed growth under simulated drought stress

NASA Astrophysics Data System (ADS)

Jinkui, FENG; Decheng, WANG; Changyong, SHAO; Lili, ZHANG; Xin, TANG

2018-03-01

The effect of different cold plasma treatments on the germination and seedling growth of alfalfa (Medicago sativa L.) seeds under simulated drought stress conditions was investigated. Polyethyleneglycol-6000 (PEG 6000)with the mass fraction of 0% (purified water), 5%, 10%, and 15% were applied to simulate the drought environment. The alfalfa seeds were treated with 15 different power levels ranged between 0-280 W for 15 s. The germination potential, germination rate, germination index, seedling root length, seedling height, and vigor index were investigated. Results indicated significant differences between treated with proper power and untreated alfalfa seeds. With the increase of treatment power, these indexes mentioned above almost presented bimodal curves. Under the different mass fractions of PEG 6000, results showed that the lower power led to increased germination, and the seedlings presented good adaptability to different drought conditions. Meanwhile, higher power levels resulted in a decreased germination rate. Seeds treated with 40 W resulted in higher germination potential, germination rate, seedling height, root length, and vigor index. Vigor indexes of the treated seeds under different PEG 6000 stresses increased by 38.68%, 43.91%, 74.34%, and 39.20% respectively compared to CK0-0, CK5-0, CK10-0, and CK15-0 (the control sample under 0%, 5%, 10%, and 15% PEG 6000). Therefore, 40 W was regarded as the best treatment in this research. Although the trend indexes of alfalfa seeds treated with the same power were statistically the same under different PEG 6000 stresses, the cold plasma treatment had a significant effect on the adaptability of alfalfa seeds in different drought environments. Thus, this kind of treatment is worth implementing to promote seed growth under drought situations.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Understanding drought propagation in the UK in the context of climatology and catchment properties

NASA Astrophysics Data System (ADS)

Barker, Lucy; Hannaford, Jamie; Bloomfield, John; Marchant, Ben

2017-04-01

Droughts are a complex natural phenomena that are challenging to plan and prepare for. The propagation of droughts through the hydrological cycle is one of many factors which contribute to this complexity, and a thorough understanding of drought propagation is crucial for informed drought management, particularly in terms of water resources management in both the short and long term. Previous studies have found that both climatological and catchment factors cause lags in drought propagation from meteorological to hydrological and hydrogeological droughts. There are strong gradients in both climatology and catchment properties across the UK. Catchments in the north and west of the UK are relatively impermeable, upland catchments with thin soils and receive the highest annual precipitation with relatively low mean annual temperatures. Conversely, in the south and east of the UK, characterised by higher mean temperatures and lower annual precipitation, catchments are underlain by a number of major aquifers (e.g. Chalk, limestone) and are typically associated with high baseflow rivers. Here we explore the effects of these gradients in climatology and catchments on the propagation of droughts. Using standardised drought indices (the Standardised Precipitation Index; the Standardised Streamflow Index; and the Standardised Groundwater Index) we analyse drought propagation characteristics for selected catchment-borehole pairs across the UK using reconstructed time series back to the 19th century. We investigate how the timing, nature and predictability of drought propagation changes across the UK, given gradients in climatology and catchment characteristics. We use probability of detection methods, usually used for forecast verification, to investigate how well precipitation and streamflow deficits predict deficits in streamflow and groundwater levels and how this varies across the UK.

How Does Drought Change With Climate Change

NASA Astrophysics Data System (ADS)

Trenberth, K. E.

2014-12-01

Large disparities among published studies have led to considerable confusion over the question of how drought is changing and how it is expected to change with global warming. As a result the IPCC AR5 assessment has watered down statements, and failed to carry out an adequate assessment of the sources of the discrepancies. Quite aside from the different definitions of drought related to meteorological (absence of precipitation), hydrological (lack of water in lakes and rivers), and agricultural (lack of soil moisture) drought, there are many indices that measure drought. Good homogeneous datasets are essential to assess changes over time, but are often not available. Simpler indices may miss effects of certain physical processes, such as evapotranspiration (ET). The Palmer Drought Severity Index (PDSI) has been much maligned but has considerable merit because it can accommodate different ET formulations (e.g., Thornthwaite vs Penman-Monteith), it can be self calibrating to accommodate different regions, and it carries out a crude moisture balance. This is in contrast to simpler indices, such as the Standardized Precipitation Index, which provides only a measure of moisture supply, or the Standardized Precipitation Evapotranspiration Index, which also includes potential (but not actual) ET. The largest source of drought variations is ENSO: during La Niña more rain falls on land while during El Niño most precipitation is over the Pacific Ocean, exposing more land to drought conditions. It is essential to account for interannual and inter-decadal variability in assessing changes in drought with climate change. Yet drought is one time on land when effects accumulate, with huge consequences for wild fire risk. It is important to ask the right questions in dealing with drought.

Identification of the influencing factors on groundwater drought in Bangladesh

NASA Astrophysics Data System (ADS)

Touhidul Mustafa, Syed Md.; Huysmans, Marijke

2015-04-01

Groundwater drought is a specific type of drought that concerns groundwater bodies. It may have a significant adverse effect on the socio-economic, agricultural, and environmental conditions. Investigating the effect of response different climatic and manmade factors on groundwater drought provides essential information for sustainable planning and management of water resources. The aim of this study is to identify the influencing factors on groundwater drought in a drought prone region in Bangladesh to understand the forcing mechanisms. The Standardised Precipitation Index (SPI) and Reconnaissance Drought Index (RDI) have been used to quantify the aggregated deficit between precipitation and the evaporative demand of the atmosphere. The influence of land use patterns on the groundwater drought has been identified by calculating spatially distributed groundwater recharge as a function of land use. The result shows that drought intensity is more severe during the dry season (November to April) compared to the rainy season (May to October). The evapotranspiration and rainfall deficit has a significant effect on meteorological drought which has a direct relation with groundwater drought. Urbanization results in a decrease of groundwater recharge which increases groundwater drought severity. Overexploitation of groundwater for irrigation and recurrent meteorological droughts are the main causes of groundwater drought in the study area. Efficient irrigation management is essential to reduce the growing pressure on groundwater resources and ensure sustainable water management. More detailed studies on climate change and land use change effects on groundwater drought are recommended. Keywords: Groundwater drought, SPI & RDI, Spatially distributed groundwater recharge, Irrigation, Bangladesh

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

PubMed

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

2016-10-07

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

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

PubMed Central

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

2016-01-01

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

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.

Index-Based Insurance Contracts to FOSTER Cooperation Between Agents Exposed to Uncorrelated Drought and Flooding Risks

NASA Astrophysics Data System (ADS)

Denaro, S.; Giuliani, M.; Castelletti, A.; Characklis, G. W.

2017-12-01

Worldwide, conflict over shared water resources is exacerbated by population growth, economic development and climate change. In multi-purpose water systems, stakeholders can face higher financial risks as a consequence of increased hydrological uncertainty and recurrent extreme events. In this context, a financial hedging tool able to bundle together the uncorrelated risks faced by different stakeholders may be an efficient solution to both foster cooperation and manage the financial losses associated with extreme events. In this work we explore the potential of risk diversification strategies involving index-based insurance joint contract solutions, to manage financial risk in a multi-purpose water system prone to both drought and flood risk. Risk diversification can allow for reduced insurance premiums in situations in which the bundled risks are entirely, or mostly, uncorrelated. Jointly covering flood and drought related risks from competing users in the same geographic area represents a novel application. The approach is demonstrated using a case study on Lake Maggiore, a regulated lake whose management is highly controversial due to numerous and competing human activities. In particular we focus on the ongoing conflict among the lakeshore population, affected by flood risk, and the downstream farmers' districts, facing drought related losses. Results are promising and indicate that bundling uncorrelated risks from competing users is beneficial to both promoting insurance premium affordability and facilitating collaboration schemes at the catchment scale.

The 2010 Russian Drought Impact on Satellite Measurements of Solar-Induced Chlorophyll Fluorescence: Insights from Modeling and Comparisons with the Normalized Differential Vegetation Index (NDVI)

NASA Technical Reports Server (NTRS)

Yoshida, Y.; Joiner, J.; Tucker, C.; Berry, J.; Lee, J. -E.; Walker, G.; Reichle, R.; Koster, R.; Lyapustin, A.; Wang, Y.

2015-01-01

We examine satellite-based measurements of chlorophyll solar-induced fluorescence (SIF) over the region impacted by the Russian drought and heat wave of 2010. Like the popular Normalized Difference Vegetation Index (NDVI) that has been used for decades to measure photosynthetic capacity, SIF measurements are sensitive to the fraction of absorbed photosynthetically-active radiation (fPAR). However, in addition, SIF is sensitive to the fluorescence yield that is related to the photosynthetic yield. Both SIF and NDVI from satellite data show drought-related declines early in the growing season in 2010 as compared to other years between 2007 and 2013 for areas dominated by crops and grasslands. This suggests an early manifestation of the dry conditions on fPAR. We also simulated SIF using a global land surface model driven by observation-based meteorological fields. The model provides a reasonable simulation of the drought and heat impacts on SIF in terms of the timing and spatial extents of anomalies, but there are some differences between modeled and observed SIF. The model may potentially be improved through data assimilation or parameter estimation using satellite observations of SIF (as well as NDVI). The model simulations also offer the opportunity to examine separately the different components of the SIF signal and relationships with Gross Primary Productivity (GPP).

Toward an index of desiccation times to tree mortality under drought

USDA-ARS?s Scientific Manuscript database

Research in plant hydraulics has provided important insights into plant responses to drought and species absolute drought tolerance. However our ability to predict when plants will die under extreme drought may be limited by a lack of knowledge with regards to the dynamics of plant desiccation from ...

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

Statistic versus stochastic characterization of persistent droughts

NASA Astrophysics Data System (ADS)

Gonzalez-Perez, J.; Valdes, J. B.

2005-12-01

Droughts are one of more devastating natural disasters. A drought event is always related with deficiency in precipitation over a time period. As longer are the drought periods, larger are the damages associated with, following a potential relationship. Additionally, the extension covered by an event also increases its impact, because it makes difficult to compensate the deficit from neighbourhood water resources. Therefore, the characterization of a drought by its persistent deficit, and the area over which it extends are main points to be carried on. The Standardized Precipitation Index (SPI) provides a statistical characterization of the deficits. Its computation, for different aggregation time scales, allows a persistence evaluation. Another more recent statistic that may be applied in drought characterization is the extreme persistent probability function (e.p.f.), which characterizes the persistence of extreme realizations in a random sequence. This work presents an analysis of the differences in performance of the SPI and the e.p.f. in the statistical characterization of a drought event. The inclusion of the persistency directly in the statistic gives to the e.p.f. an advantage over the SPI. Furthermore, the relationship between the e.p.f. and its mean frequency of recurrence is known. Thus, the e.p.f. may be applied to provide either statistic or stochastic characterization of a drought event. Both criteria were compared, showing that the stochastic characterization produces a better drought indicator. The stochastic characterization using the e.p.f. as a criterion yields the new Drought Frequency Index (DFI). The index is applicable to any random water related variable to identify drought events. Its main advantages over the SPI are the direct inclusion of persistence, and its larger robustness to the time scale. To incorporate the spatial extension in the characterization of a drought event, the new DFI may also be evaluated to characterize the drought spatial-temporal development using DFI-maps. Case studies in Spain and the USA support the advantages of the e.p.f.

Deploying a Proximal Sensing Cart to Identify Drought-Adaptive Traits in Upland Cotton for High-Throughput Phenotyping

PubMed Central

Thompson, Alison L.; Thorp, Kelly R.; Conley, Matthew; Andrade-Sanchez, Pedro; Heun, John T.; Dyer, John M.; White, Jeffery W.

2018-01-01

Field-based high-throughput phenotyping is an emerging approach to quantify difficult, time-sensitive plant traits in relevant growing conditions. Proximal sensing carts represent an alternative platform to more costly high-clearance tractors for phenotyping dynamic traits in the field. A proximal sensing cart and specifically a deployment protocol, were developed to phenotype traits related to drought tolerance in the field. The cart-sensor package included an infrared thermometer, ultrasonic transducer, multi-spectral reflectance sensor, weather station, and RGB cameras. The cart deployment protocol was evaluated on 35 upland cotton (Gossypium hirsutum L.) entries grown in 2017 at Maricopa, AZ, United States. Experimental plots were grown under well-watered and water-limited conditions using a (0,1) alpha lattice design and evaluated in June and July. Total collection time of the 0.87 hectare field averaged 2 h and 27 min and produced 50.7 MB and 45.7 GB of data from the sensors and RGB cameras, respectively. Canopy temperature, crop water stress index (CWSI), canopy height, normalized difference vegetative index (NDVI), and leaf area index (LAI) differed among entries and showed an interaction with the water regime (p < 0.05). Broad-sense heritability (H2) estimates ranged from 0.097 to 0.574 across all phenotypes and collections. Canopy cover estimated from RGB images increased with counts of established plants (r = 0.747, p = 0.033). Based on the cart-derived phenotypes, three entries were found to have improved drought-adaptive traits compared to a local adapted cultivar. These results indicate that the deployment protocol developed for the cart and sensor package can measure multiple traits rapidly and accurately to characterize complex plant traits under drought conditions. PMID:29868041

500-year April-September droughts in the Czech Lands based on documentary data and instrumental records

NASA Astrophysics Data System (ADS)

Řezníčková, Ladislava; Brázdil, Rudolf; Trnka, Miroslav; Dobrovolný, Petr; Kotyza, Oldřich; Štěpánek, Petr; Zahradníček, Pavel; Valášek, Hubert

2013-04-01

This paper analyses temporal and spatial variability of April-September (the vegetation period) droughts in the Czech Lands over the last 500 years. The study is based on different types of documentary data (e.g. chronicles, newspapers, economic sources, weather diaries) covering the pre-instrumental period AD 1501-1804 and on the systematic instrumental meteorological measurements afterwards. Historical-climatological database of the Czech Lands is used for the study of the duration and intensity of drought episodes based on the series of precipitation indices created from documentary data in a 7-degree scale from -3 (extremely dry) to +3 (extremely wet). For the instrumental period of 1805-2012 Palmer's Z-index and PDSI series for mean Czech temperature and precipitation series are used (they were calculated from homogeneous series of 10 and 14 stations respectively). Consequently the 500-year chronology of drought episodes derived from documentary and instrumental data is compiled and the temporal (frequency, seasonality and intensity) and spatial variability of droughts in the Czech Lands from AD 1501 is analysed. The most outstanding drought events are selected and analysed in detail also with respect to their human impacts. The results obtained for the Czech Lands are compared with drought episodes known in Central Europe from other studies and are evaluated with respect to climate variability in Central Europe during the last 500 years (this research is supported by projects InterDrought no. CZ.1.07/2.3.00/20.0248, and GA CR no. P209/11/0956).

A parametric multivariate drought index and its application in the attribution and projection of flash drought change in China

NASA Astrophysics Data System (ADS)

Yuan, X.; Wang, L.; Zhang, M.

2017-12-01

Rainfall deficit in the crop growing seasons is usually accompanied by heat waves. Abnormally high temperature increases evapotranspiration and decreases soil moisture rapidly, and ultimately results in a type of drought with a rapid onset, short duration but devastating impact, which is called "Flash drought". With the increase in global temperature, flash drought is expected to occur more frequently. However, there is no consensus on the definition of flash drought so far. Moreover, large uncertainty exists in the estimation of the flash drought and its trend, and the underlying mechanism for its long-term change is not clear. In this presentation, a parametric multivariate drought index that characterizes the joint probability distribution of key variables of flash drought will be developed, and the historical changes in flash drought over China will be analyzed. In addition, a set of land surface model simulations driven by IPCC CMIP5 models with different forcings and future scenarios, will be used for the detection and attribution of flash drought change. This study is targeted at quantifying the influences of natural and anthropogenic climate change on the flash drought change, projecting its future change as well as the corresponding uncertainty, and improving our understanding of the variation of flash drought and its underlying mechanism in a changing climate.

Spatial patterns of drought persistence in East China

NASA Astrophysics Data System (ADS)

Meng, L.; Ford, T.

2017-12-01

East China has experienced a number of severe droughts in recent decades. Understanding the characteristics of droughts and their persistence will provide operational guidelines for water resource management and agricultural production. This study uses a logistic regression model to measure the probability of drought occurrence in the current season given the previous season's Standardized Precipitation Index (SPI) and Southern Oscillation Index (SOI) as well as drought persistence. Results reveal large spatial and seasonal variations in the relationship between the previous season's SPI and the drought occurrence probability in a given season. The drought persistence averaged over the entire study area for all the four seasons is approximately 34% with large variations from season to season and from region to region. The East and Northeast regions have the largest summer drought persistence ( 40%) and lowest fall drought persistence ( 28%). The spatial pattern in winter and spring drought persistence is dissimilar with stronger winter and weaker spring drought persistence in the Southwest and Northeast relative to other regions. Logistic regression analysis indicates a stronger negative relationship in summer-to-fall (or between fall drought occurrence and summer SPI) than other inter-season relationships. This study demonstrates that the impact of previous season SPI and SOI on current season drought varies substantially from region to region and from season to season. This study also shows stronger drought persistence in summer than in other seasons. In other words, the probability of fall drought occurrence is closely related to summer moisture conditions in the East China.

Examining Severe Drought-Induced Vegetation Change and its Influence on Water Resources

NASA Astrophysics Data System (ADS)

White, A. B.; Springer, E. P.; Vivoni, E. R.

2007-12-01

A "global-change-type" drought that occurred in the southwestern U.S. from 2000 to 2003, accompanied by increased temperatures and bark beetle infestations, induced large-scale woodland overstory mortality, the consequent redistribution of water, radiation, and nutrients, as well as modification of the ecosystem phenology. Our objectives in this research are to examine these vegetation changes in detail and to determine whether they translated to changes in hydrological processes. We chose the Rio Ojo Caliente, a subbasin of the Rio Grande, as a study site since a significant portion of the woodland ecosystem (piñon-juniper) was affected. Examining a remotely-sensed vegetation index (1-km AVHRR NDVI from 1989 to 2006), there is an increasing trend in the mean NDVI from 1989 to 1998 (pre-drought period), a decreasing trend from 1999 to 2003 (drought period), and a dramatic increasing trend from 2004 to 2006 (post-drought period) in which the mean NDVI rebounds to pre- drought magnitudes. Streamflow records from 1932 to 2006 show the watershed to be primarily spring snowmelt-driven, although monsoonal summer precipitation also plays a significant role. We compare the temporal variability in the streamflow to the NDVI, including the mean, anomalies from the mean, and seasonally- based duration curves, and find significant correlations (correlation coefficient ρ = -0.61) between the streamflow and NDVI at approximately a three-month lag (NDVI lagging streamflow). In analyzing the three phases of the drought, the correlation is slightly stronger during the pre-drought (ρ = -0.64) and drought (ρ = -0.65) periods, yet markedly stronger during the post-drought period (ρ = -0.74). This suggests that the coupling between vegetation water use and streamflow is tighter after the drought. This may be attributable to the reduction in the less-responsive overstory (pinñon mortality) and increase in the more-responsive understory (grasses and shrubs exploiting newly available resources). Temporal patterns in gauge-based precipitation (frozen and unfrozen) and air temperature, and spatial-temporal patterns in PRISM precipitation, air temperature, and a soil moisture index are also compared to the NDVI. While the vegetation composition was altered to a great degree in the Rio Ojo Caliente Basin, the system rapidly recovered both photosynthetically and hydrologically during the post-drought wet period, although the dynamic between vegetation water use and streamflow was slightly altered. The aim of this research is to explore the consequences of a severe drought married with elevated temperatures on vegetation and water resources. As the intensity and frequency of droughts are expected to increase in the southwestern U.S. with rising temperatures (IPCC 2007), this research contributes to our knowledge of ecosystem and hydrologic response to the changing climate.

Future opportunities and challenges in remote sensing of drought

USGS Publications Warehouse

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

2012-01-01

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

Future Opportunities and Challenges in Remote Sensing of Drought

NASA Technical Reports Server (NTRS)

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

2011-01-01

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

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. EDI and spatially downscaled soil moisture products were later used with MODIS 16 days NDVI product as key elements to assess and predict agricultural drought in irrigated and rain-fed agricultural systems in Bundelkhand region of India. Meteorological drought, soil moisture deficiency and NDVI degradation were inhabited for each and every pixel of the image in GIS environment, for agricultural impact assessment at a 16 day temporal scale for Rabi seasons (October-April) between years 2000 to 2009. Based on the statistical analysis, good correlations were found among the parameters EDI and soil moisture anomaly; NDVI anomaly and soil moisture anomaly lagged to 16 days and these results were exploited for the development of a linear prediction model. The predictive capability of the developed model was validated on the basis of spatial distribution of predicted NDVI which was compared with MODIS NDVI product in the beginning of preceding Rabi season (Oct-Dec of 2010).The predictions of the model were based on future meteorological data (year 2010) and were found to be yielding good results. The developed model have good predictive capability based on future meteorological data (rainfall data) availability, which enhances its utility in analyzing future Agricultural conditions if meteorological data is available.

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

Understanding the land-atmospheric interaction in drought forecast from CFSv2 for the 2011 Texas and 2012 Upper Midwest US droughts

NASA Astrophysics Data System (ADS)

Zhang, Y.; Roundy, J. K.; Ek, M. B.; Wood, E. F.

2015-12-01

Prediction and thus preparedness in advance of hydrological extremes, such as drought and flood events, is crucial for proactively reducing their social and economic impacts. In the summers of 2011 Texas, and 2012 the Upper Midwest, experienced intense droughts that affected crops and the food market in the US. It is expected that seasonal forecasts with sufficient skill would reduce the negative impacts through planning and preparation. However, the forecast skill from models such as Climate Forecast System Version 2 (CFSv2) from National Centers for Environmental Prediction (NCEP) is low over the US, especially during the warm season (Jun - Sep), which restricts their practical use for drought prediction. This study analyzes the processes that lead to premature termination of 2011 and 2012 US summer droughts in CFSv2 forecast resulting in its low forecast skill. Using the North American Land Data Assimilation System version 2 (NLDAS2) and Climate Forecast System Reanalysis (CFSR) as references, this study investigates the forecast skills of CFSv2 initialized at 00, 06, 12, 18z from May 15 - 31 (leads out to September) for each event in terms of land-atmosphere interaction, through a recently developed Coupling Drought Index (CDI), which is based on the Convective Triggering Potential-Humidity Index-soil moisture (CTP-HI-SM) classification of four climate regimes: wet coupling, dry coupling, transitional and atmospherically controlled. A recycling model is used to trace the moisture sources in the CFSv2 forecasts of anomalous precipitation, which lead to the breakdown of drought conditions and a lack of drought forecasting skills. This is then compared with tracing the moisture source in CFSR with the same recycling model, which is used as the verification for the same periods. This helps to identify the parameterization that triggered precipitation in CFSv2 during 2011 and 2012 summer in the US thus has the potential to improve the forecast skill of CSFv2.

Forest resilience to drought varies across biomes.

PubMed

Gazol, Antonio; Camarero, Jesus Julio; Vicente-Serrano, Sergio M; Sánchez-Salguero, Raúl; Gutiérrez, Emilia; de Luis, Martin; Sangüesa-Barreda, Gabriel; Novak, Klemen; Rozas, Vicente; Tíscar, Pedro A; Linares, Juan C; Martín-Hernández, Natalia; Martínez Del Castillo, Edurne; Ribas, Montse; García-González, Ignacio; Silla, Fernando; Camisón, Alvaro; Génova, Mar; Olano, José M; Longares, Luis A; Hevia, Andrea; Tomás-Burguera, Miquel; Galván, J Diego

2018-05-01

Forecasted increase drought frequency and severity may drive worldwide declines in forest productivity. Species-level responses to a drier world are likely to be influenced by their functional traits. Here, we analyse forest resilience to drought using an extensive network of tree-ring width data and satellite imagery. We compiled proxies of forest growth and productivity (TRWi, absolutely dated ring-width indices; NDVI, Normalized Difference Vegetation Index) for 11 tree species and 502 forests in Spain corresponding to Mediterranean, temperate, and continental biomes. Four different components of forest resilience to drought were calculated based on TRWi and NDVI data before, during, and after four major droughts (1986, 1994-1995, 1999, and 2005), and pointed out that TRWi data were more sensitive metrics of forest resilience to drought than NDVI data. Resilience was related to both drought severity and forest composition. Evergreen gymnosperms dominating semi-arid Mediterranean forests showed the lowest resistance to drought, but higher recovery than deciduous angiosperms dominating humid temperate forests. Moreover, semi-arid gymnosperm forests presented a negative temporal trend in the resistance to drought, but this pattern was absent in continental and temperate forests. Although gymnosperms in dry Mediterranean forests showed a faster recovery after drought, their recovery potential could be constrained if droughts become more frequent. Conversely, angiosperms and gymnosperms inhabiting temperate and continental sites might have problems to recover after more intense droughts since they resist drought but are less able to recover afterwards. © 2018 John Wiley & Sons Ltd.

Managing water utility financial risks through third-party index insurance contracts

NASA Astrophysics Data System (ADS)

Zeff, Harrison B.; Characklis, Gregory W.

2013-08-01

As developing new supply capacity has become increasingly expensive and difficult to permit (i.e., regulatory approval), utilities have become more reliant on temporary demand management programs, such as outdoor water use restrictions, for ensuring reliability during drought. However, a significant fraction of water utility income is often derived from the volumetric sale of water, and such restrictions can lead to substantial revenue losses. Given that many utilities set prices at levels commensurate with recovering costs, these revenue losses can leave them financially vulnerable to budgetary shortfalls. This work explores approaches for mitigating drought-related revenue losses through the use of third-party financial insurance contracts based on streamflow indices. Two different types of contracts are developed, and their efficacy is compared against two more traditional forms of financial hedging used by water utilities: Drought surcharges and contingency funds (i.e., self-insurance). Strategies involving each of these approaches, as well as their use in combination, are applied under conditions facing the water utility serving Durham, North Carolina. A multireservoir model provides information on the scale and timing of droughts, and the financial effects of these events are simulated using detailed data derived from utility billing records. Results suggest that third-party index insurance contracts, either independently or in combination with more traditional hedging tools, can provide an effective means of reducing a utility's financial vulnerability to drought.

Standardized Precipitation Index (SPI) over the Mediterranean region based on high resolution gridded data.

NASA Astrophysics Data System (ADS)

Polychroni, Iliana; Nastos, Panagiotis

2017-04-01

Mediterranean water resource system is heavily influenced by changes in climate conditions, which in turns affect significantly the socioeconomic development, specifically over coastal areas. Taking into consideration that the surface temperature is projected to rise over the 21st century and the mean precipitation is likely to decrease in mid-latitude dry regions, according to IPCC 2014, we confronted the challenge to study the drought over the Mediterranean region by means of the Standardized Precipitation Index (SPI), defined as the difference from the mean for a specified time period divided by the standard deviation, where the mean and standard deviation are determined from past records. Drought is a long-range phenomenon that affects the Mediterranean. The drought not only affects food production but also has severe environmental, economic and social impacts. The objective of this study is to assess and analyze the spatio-temporal evolution of the SPI for 3-, 6-, 9-, 12- month timescales, during the period 1950-2015. For this purpose, we processed high resolution gridded daily precipitation datasets (0.25° x 0.25°), based on the E-OBS dataset from ECA&D. Mean SPI patterns and trends for the whole examined period, as well as successive 30-year periods, were assessed by using R-project. Moreover, the influence of the well-known atmospheric circulation index of the wider region of Europe, namely the North Atlantic Oscillation Index (NAOI), on the SPI over the Mediterranean was considered necessary to evaluate, because NAOI strongly modulates precipitation over Europe and the Mediterranean.

Performance of the Enhanced Vegetation Index to Detect Inner-annual Dry Season and Drought Impacts on Amazon Forest Canopies

NASA Astrophysics Data System (ADS)

Brede, B.; Verbesselt, J.; Dutrieux, L.; Herold, M.

2015-04-01

The Amazon rainforests represent the largest connected forested area in the tropics and play an integral role in the global carbon cycle. In the last years the discussion about their phenology and response to drought has intensified. A recent study argued that seasonality in greenness expressed as Enhanced Vegetation Index (EVI) is an artifact of variations in sun-sensor geometry throughout the year. We aimed to reproduce these results with the Moderate-Resolution Imaging Spectroradiometer (MODIS) MCD43 product suite, which allows modeling the Bidirectional Reflectance Distribution Function (BRDF) and keeping sun-sensor geometry constant. The derived BRDF-adjusted EVI was spatially aggregated over large areas of central Amazon forests. The resulting time series of EVI spanning the 2000-2013 period contained distinct seasonal patterns with peak values at the onset of the dry season, but also followed the same pattern of sun geometry expressed as Solar Zenith Angle (SZA). Additionally, we assessed EVI's sensitivity to precipitation anomalies. For that we compared BRDF-adjusted EVI dry season anomalies to two drought indices (Maximum Cumulative Water Deficit, Standardized Precipitation Index). This analysis covered the whole of Amazonia and data from the years 2000 to 2013. The results showed no meaningful connection between EVI anomalies and drought. This is in contrast to other studies that investigate the drought impact on EVI and forest photosynthetic capacity. The results from both sub-analyses question the predictive power of EVI for large scale assessments of forest ecosystem functioning in Amazonia. Based on the presented results, we recommend a careful evaluation of the EVI for applications in tropical forests, including rigorous validation supported by ground plots.

Predictive Skill of Meteorological Drought Based on Multi-Model Ensemble Forecasts: A Real-Time Assessment

NASA Astrophysics Data System (ADS)

Chen, L. C.; Mo, K. C.; Zhang, Q.; Huang, J.

2014-12-01

Drought prediction from monthly to seasonal time scales is of critical importance to disaster mitigation, agricultural planning, and multi-purpose reservoir management. Starting in December 2012, NOAA Climate Prediction Center (CPC) has been providing operational Standardized Precipitation Index (SPI) Outlooks using the North American Multi-Model Ensemble (NMME) forecasts, to support CPC's monthly drought outlooks and briefing activities. The current NMME system consists of six model forecasts from U.S. and Canada modeling centers, including the CFSv2, CM2.1, GEOS-5, CCSM3.0, CanCM3, and CanCM4 models. In this study, we conduct an assessment of the predictive skill of meteorological drought using real-time NMME forecasts for the period from May 2012 to May 2014. The ensemble SPI forecasts are the equally weighted mean of the six model forecasts. Two performance measures, the anomaly correlation coefficient and root-mean-square errors against the observations, are used to evaluate forecast skill.Similar to the assessment based on NMME retrospective forecasts, predictive skill of monthly-mean precipitation (P) forecasts is generally low after the second month and errors vary among models. Although P forecast skill is not large, SPI predictive skill is high and the differences among models are small. The skill mainly comes from the P observations appended to the model forecasts. This factor also contributes to the similarity of SPI prediction among the six models. Still, NMME SPI ensemble forecasts have higher skill than those based on individual models or persistence, and the 6-month SPI forecasts are skillful out to four months. The three major drought events occurred during the 2012-2014 period, the 2012 Central Great Plains drought, the 2013 Upper Midwest flash drought, and 2013-2014 California drought, are used as examples to illustrate the system's strength and limitations. For precipitation-driven drought events, such as the 2012 Central Great Plains drought, NMME SPI forecasts perform well in predicting drought severity and spatial patterns. For fast-developing drought events, such as the 2013 Upper Midwest flash drought, the system failed to capture the onset of the drought.

Applicability of predictive models of drought-induced tree mortality between the midwest and northeast United States

Treesearch

Eric J. Gustafson

2014-01-01

Regression models developed in the upper Midwest (United States) to predict drought-induced tree mortality from measures of drought (Palmer Drought Severity Index) were tested in the northeastern United States and found inadequate. The most likely cause of this result is that long drought events were rare in the Northeast during the period when inventory data were...

A nonparametric standardized runoff index for characterizing hydrological drought on the Loess Plateau, China

NASA Astrophysics Data System (ADS)

Wu, Jingwen; Miao, Chiyuan; Tang, Xu; Duan, Qingyun; He, Xiaojia

2018-02-01

Drought is one of the world's most recurrent and destructive hazards, and the evolution of drought events has become increasingly complex against a background of climate change and changing human activities. Over the last five decades, there have been frequent droughts on the Loess Plateau in China. In this study, we used the nonparametric standardized runoff index (NSRI) to investigate the temporal characteristics of hydrological drought in 17 Loess Plateau catchments during the period 1961-2013. Furthermore, we used a cross-wavelet transform to reveal linkages between an El Niño-Southern Oscillation (ENSO) index and the NSRI series. The primary results indicated that the annual and seasonal NSRI series displayed statistically significantly downward trends in all catchments, with the only exception being the winter NSRI series in Yanhe. Furthermore, our analyses showed downward trends persisting into the future in all 17 catchments except Yanhe. We also found that, overall, the risk of hydrological drought was high on the Loess Plateau, with the mean duration at the seasonal scale exceeding 4 months and the mean duration at the annual scale exceeding 12 months. Moreover, during recent years, the trend towards hydrological drought was greater in the spring than in other seasons. ENSO events were closely associated with annual and seasonal hydrological drought on the Loess Plateau, and the impact of ENSO events was stronger in the southeast of the plateau than the northwest at both seasonal and annual scales. These results may provide valuable information about the evolutionary characteristics of hydrological drought across the Loess Plateau and may also be useful for predicting and mitigating future hydrological drought on the plateau.

Remote sensing monitoring the spatio-temporal changes of aridification in the Mongolian Plateau based on the general Ts-NDVI space, 1981-2012

NASA Astrophysics Data System (ADS)

Cao, Xiaoming; Feng, Yiming; Wang, Juanle

2017-06-01

This paper has developed a general Ts-NDVI triangle space with vegetation index time-series data from AVHRR and MODIS to monitor soil moisture in the Mongolian Plateau during 1981-2012, and studied the spatio-temporal variations of drought based on the temperature vegetation dryness index (TVDI). The results indicated that (1) the developed general Ts-NDVI space extracted from the AVHRR and MODIS remote sensing data would be an effective method to monitor regional drought, moreover, it would be more meaningful if the single time Ts-NDVI space showed an unstable condition; (2) the inverted TVDI was expected to reflect the water deficit in the study area. It was found to be in close negative agreement with precipitation and 10 cm soil moisture; (3) in the Mongolian Plateau, TVDI presented a zonal distribution with changes in land use/land cover types, vegetation cover and latitude. The soil moisture is low in bare land, construction land and grassland. During 1981-2012, drought was widely spread throughout the plateau, and aridification was obvious in the study period. Vegetation degradation, overgrazing, and climate warming could be considered as the main reasons.

Correlation between Annual Corn Crop per Hectare in Croatia and Drought Indices for Zagreb-Gric Observatory

NASA Astrophysics Data System (ADS)

Pandzic, Kreso; Likso, Tanja

2017-04-01

Correlation coefficients between annual corn crop per hectare in Croatia and 9-month Standardized Precipitation Index (SPI) and Palmer Drought Severity Index (PDSI) for Zagreb - Gric for August are shown as significant. The results indicate that there is also a significant correlation between those drought indices and drought damages. Thus a forecast of the indices for August could be used for estimation e.g. annual corn crop per hectare in Croatia. Better results could be expected if statistical relationship between annual corn crops per hectare will be considered on county level instead the whole Croatia and indices calculated for weather stations for the same county. Effective way for reduction of drought damages is irrigation which need to be significantly improved in future in Croatia

Review of complex networks application in hydroclimatic extremes with an implementation to characterize spatio-temporal drought propagation in continental USA

NASA Astrophysics Data System (ADS)

Konapala, Goutam; Mishra, Ashok

2017-12-01

The quantification of spatio-temporal hydroclimatic extreme events is a key variable in water resources planning, disaster mitigation, and preparing climate resilient society. However, quantification of these extreme events has always been a great challenge, which is further compounded by climate variability and change. Recently complex network theory was applied in earth science community to investigate spatial connections among hydrologic fluxes (e.g., rainfall and streamflow) in water cycle. However, there are limited applications of complex network theory for investigating hydroclimatic extreme events. This article attempts to provide an overview of complex networks and extreme events, event synchronization method, construction of networks, their statistical significance and the associated network evaluation metrics. For illustration purpose, we apply the complex network approach to study the spatio-temporal evolution of droughts in Continental USA (CONUS). A different drought threshold leads to a new drought event as well as different socio-economic implications. Therefore, it would be interesting to explore the role of thresholds on spatio-temporal evolution of drought through network analysis. In this study, long term (1900-2016) Palmer drought severity index (PDSI) was selected for spatio-temporal drought analysis using three network-based metrics (i.e., strength, direction and distance). The results indicate that the drought events propagate differently at different thresholds associated with initiation of drought events. The direction metrics indicated that onset of mild drought events usually propagate in a more spatially clustered and uniform approach compared to onsets of moderate droughts. The distance metric shows that the drought events propagate for longer distance in western part compared to eastern part of CONUS. We believe that the network-aided metrics utilized in this study can be an important tool in advancing our knowledge on drought propagation as well as other hydroclimatic extreme events. Although the propagation of droughts is investigated using the network approach, however process (physics) based approaches is essential to further understand the dynamics of hydroclimatic extreme events.

Climate change and water availability for vulnerable agriculture

NASA Astrophysics Data System (ADS)

Dalezios, Nicolas; Tarquis, Ana Maria

2017-04-01

Climatic projections for the Mediterranean basin indicate that the area will suffer a decrease in water resources due to climate change. The key climatic trends identified for the Mediterranean region are continuous temperature increase, further drying with precipitation decrease and the accentuation of climate extremes, such as droughts, heat waves and/or forest fires, which are expected to have a profound effect on agriculture. Indeed, the impact of climate variability on agricultural production is important at local, regional, national, as well as global scales. Agriculture of any kind is strongly influenced by the availability of water. Climate change will modify rainfall, evaporation, runoff, and soil moisture storage patterns. Changes in total seasonal precipitation or in its pattern of variability are both important. Similarly, with higher temperatures, the water-holding capacity of the atmosphere and evaporation into the atmosphere increase, and this favors increased climate variability, with more intense precipitation and more droughts. As a result, crop yields are affected by variations in climatic factors, such as air temperature and precipitation, and the frequency and severity of the above mentioned extreme events. The aim of this work is to briefly present the main effects of climate change and variability on water resources with respect to water availability for vulnerable agriculture, namely in the Mediterranean region. Results of undertaken studies in Greece on precipitation patterns and drought assessment using historical data records are presented. Based on precipitation frequency analysis, evidence of precipitation reductions is shown. Drought is assessed through an agricultural drought index, namely the Vegetation Health Index (VHI), in Thessaly, a drought-prone region in central Greece. The results justify the importance of water availability for vulnerable agriculture and the need for drought monitoring in the Mediterranean basin as part of an integrated climate adaptation strategy.

Suicide and drought in New South Wales, Australia, 1970–2007

PubMed Central

Hanigan, Ivan C.; Butler, Colin D.; Kokic, Philip N.; Hutchinson, Michael F.

2012-01-01

There is concern in Australia that droughts substantially increase the incidence of suicide in rural populations, particularly among male farmers and their families. We investigated this possibility for the state of New South Wales (NSW), Australia between 1970 and 2007, analyzing data on suicides with a previously established climatic drought index. Using a generalized additive model that controlled for season, region, and long-term suicide trends, we found an increased relative risk of suicide of 15% (95% confidence interval, 8%–22%) for rural males aged 30–49 y when the drought index rose from the first quartile to the third quartile. In contrast, the risk of suicide for rural females aged >30 y declined with increased values of the drought index. We also observed an increased risk of suicide in spring and early summer. In addition there was a smaller association during unusually warm months at any time of year. The spring suicide increase is well documented in nontropical locations, although its cause is unknown. The possible increased risk of suicide during drought in rural Australia warrants public health focus and concern, as does the annual, predictable increase seen each spring and early summer. Suicide is a complex phenomenon with many interacting social, environmental, and biological causal factors. The relationship between drought and suicide is best understood using a holistic framework. Climate change projections suggest increased frequency and severity of droughts in NSW, accompanied and exacerbated by rising temperatures. Elucidating the relationships between drought and mental health will help facilitate adaptation to climate change. PMID:22891347

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2008-05-01

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

Lack of association between drought and mental health in a cohort of 45-61 year old rural Australian women.

PubMed

Powers, Jennifer R; Dobson, Annette J; Berry, Helen L; Graves, Anna M; Hanigan, Ivan C; Loxton, Deborah

2015-12-01

To evaluate the impact of drought on the mental health of rural Australian women and those in vulnerable sub-populations: women who were more isolated, poorer and less educated; and women who had histories of chronic disease or poor mental health. Surveys were mailed in 1996, 1998, 2001, 2004 and 2008 to 6,664 women born between 1946 and1951 who were participating in the Australian Longitudinal Study on Women's Health. The surveys included the Mental Health Index of the Medical Outcomes Study Short-Form 36 (MHI). Drought was assessed by linking the latitude and longitude of women's place of residence at each survey to the Hutchinson Drought Index. Associations between MHI and drought were assessed using linear mixed-models. While 31% of the women experienced drought in 1998 and 50% experienced drought in 2007; experience of droughts was less common in the other years. Although drought varied from survey year to survey year, mental health did not vary with drought conditions for rural women or vulnerable sub-populations. These findings are contrary to the long-held assumption that droughts increase mental health problems in Australia. While similar results may not be true for men, empirical evidence (rather than assumptions) is required on associations between drought and mental health. © 2015 Public Health Association of Australia.

The Impacts of Typical Drought Events on Terrestrial Vegetation in China

NASA Astrophysics Data System (ADS)

Yang, J.; Wu, J.; Zhou, H.; Han, X.

2018-04-01

In our study, according to the statistical results of standardized precipitation evapotranspiration index (SPEI), we chose two drought events which occurred in the North China during 2001 and in the Southwest China from 2009 to 2010. And two of the Global Land Surface Satellite (GLASS) products had been used to evaluate the impacts of drought on vegetation, including the leaf area index (LAI) and the fraction of absorbed photosynthetically active radiation (FAPAR). The results show that: (1) In the development process of a drought event, the anomaly of remote sensing parameters (LAI and FAPAR) usually falls firstly and then rises as the drought changes from moderate to severe and then to moderate. This indicates that the effects of drought on vegetation remote sensing parameters are closely related to the severity of drought disaster. (2) The response of different vegetation types to the drought disaster is different. Compared with the forests, the response of grasslands to drought disaster is earlier. For example, the duration affected by drought disaster in grassland is longer 1/3 than the forests in the Southwest China. (3) Irrigation is an effective measure to mitigate the effects of drought. Irrigated croplands are less affected by drought than non-irrigated croplands and grasslands. In the North China, the decrease amplitude of irrigated croplands' remote sensing parameters is about half of non-irrigated croplands'.

Remotely-sensed detection of effects of extreme droughts on gross primary production.

PubMed

Vicca, Sara; Balzarolo, Manuela; Filella, Iolanda; Granier, André; Herbst, Mathias; Knohl, Alexander; Longdoz, Bernard; Mund, Martina; Nagy, Zoltan; Pintér, Krisztina; Rambal, Serge; Verbesselt, Jan; Verger, Aleixandre; Zeileis, Achim; Zhang, Chao; Peñuelas, Josep

2016-06-15

Severe droughts strongly impact photosynthesis (GPP), and satellite imagery has yet to demonstrate its ability to detect drought effects. Especially changes in vegetation functioning when vegetation state remains unaltered (no browning or defoliation) pose a challenge to satellite-derived indicators. We evaluated the performance of different satellite indicators to detect strong drought effects on GPP in a beech forest in France (Hesse), where vegetation state remained largely unaffected while GPP decreased substantially. We compared the results with three additional sites: a Mediterranean holm oak forest (Puéchabon), a temperate beech forest (Hainich), and a semi-arid grassland (Bugacpuszta). In Hesse, a three-year reduction in GPP following drought was detected only by the Enhanced Vegetation Index (EVI). The Photochemical Reflectance Index (PRI) also detected this drought effect, but only after normalization for absorbed light. In Puéchabon normalized PRI outperformed the other indicators, while the short-term drought effect in Hainich was not detected by any tested indicator. In contrast, most indicators, but not PRI, captured the drought effects in Bugacpuszta. Hence, PRI improved detection of drought effects on GPP in forests and we propose that PRI normalized for absorbed light is considered in future algorithms to estimate GPP from space.

Assessing vegetation response to drought in the northern Great Plains using vegetation and drought indices

USGS Publications Warehouse

Ji, Lei; Peters, Albert J.

2003-01-01

The Normalized Difference Vegetation Index (NDVI) derived from the Advanced Very High Resolution Radiometer (AVHRR) has been widely used to monitor moisture-related vegetation condition. The relationship between vegetation vigor and moisture availability, however, is complex and has not been adequately studied with satellite sensor data. To better understand this relationship, an analysis was conducted on time series of monthly NDVI (1989–2000) during the growing season in the north and central U.S. Great Plains. The NDVI was correlated to the Standardized Precipitation Index (SPI), a multiple-time scale meteorological-drought index based on precipitation. The 3-month SPI was found to have the best correlation with the NDVI, indicating lag and cumulative effects of precipitation on vegetation, but the correlation between NDVI and SPI varies significantly between months. The highest correlations occurred during the middle of the growing season, and lower correlations were noted at the beginning and end of the growing season in most of the area. A regression model with seasonal dummy variables reveals that the relationship between the NDVI and SPI is significant in both grasslands and croplands, if this seasonal effect is taken into account. Spatially, the best NDVI–SPI relationship occurred in areas with low soil water-holding capacity. Our most important finding is that NDVI is an effective indicator of vegetation-moisture condition, but seasonal timing should be taken into consideration when monitoring drought with the NDVI.

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.

Assessments of Drought Impacts on Vegetation in China with the Optimal Time Scales of the Climatic Drought Index

PubMed Central

Li, Zheng; Zhou, Tao; Zhao, Xiang; Huang, Kaicheng; Gao, Shan; Wu, Hao; Luo, Hui

2015-01-01

Drought is expected to increase in frequency and severity due to global warming, and its impacts on vegetation are typically extensively evaluated with climatic drought indices, such as multi-scalar Standardized Precipitation Evapotranspiration Index (SPEI). We analyzed the covariation between the SPEIs of various time scales and the anomalies of the normalized difference vegetation index (NDVI), from which the vegetation type-related optimal time scales were retrieved. The results indicated that the optimal time scales of needle-leaved forest, broadleaf forest and shrubland were between 10 and 12 months, which were considerably longer than the grassland, meadow and cultivated vegetation ones (2 to 4 months). When the optimal vegetation type-related time scales were used, the SPEI could better reflect the vegetation’s responses to water conditions, with the correlation coefficients between SPEIs and NDVI anomalies increased by 5.88% to 28.4%. We investigated the spatio-temporal characteristics of drought and quantified the different responses of vegetation growth to drought during the growing season (April–October). The results revealed that the frequency of drought has increased in the 21st century with the drying trend occurring in most of China. These results are useful for ecological assessments and adapting management steps to mitigate the impact of drought on vegetation. They are helpful to employ water resources more efficiently and reduce potential damage to human health caused by water shortages. PMID:26184243

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.

Drought impacts and resilience on crops via evapotranspiration estimations

NASA Astrophysics Data System (ADS)

Timmermans, Joris; Asadollahi Dolatabad, Saeid

2015-04-01

Currently, the global needs for food and water is at a critical level. It has been estimated that 12.5 % of the global population suffers from malnutrition and 768 million people still do not have access to clean drinking water. This need is increasing because of population growth but also by climate change. Changes in precipitation patterns will result either in flooding or droughts. Consequently availability, usability and affordability of water is becoming challenge and efficient use of water and water management is becoming more important, particularly during severe drought events. Drought monitoring for agricultural purposes is very hard. While meteorological drought can accurately be monitored using precipitation only, estimating agricultural drought is more difficult. This is because agricultural drought is dependent on the meteorological drought, the impacts on the vegetation, and the resilience of the crops. As such not only precipitation estimates are required but also evapotranspiration at plant/plot scale. Evapotranspiration (ET) describes the amount of water evaporated from soil and vegetation. As 65% of precipitation is lost by ET, drought severity is highly linked with this variable. In drought research, the precise quantification of ET and its spatio-temporal variability is therefore essential. In this view, remote sensing based models to estimate ET, such as SEBAL and SEBS, are of high value. However the resolution of current evapotranspiration products are not good enough for monitoring the impact of the droughts on the specific crops. This limitation originates because plot scales are in general smaller than the resolution of the available satellite ET products. As such remote sensing estimates of evapotranspiration are always a combination of different land surface types and cannot be used for plant health and drought resilience studies. The goal of this research is therefore to enable adequate resolutions of daily evapotranspiration estimates for monitoring crop health during the severe drought events. The presentation will provide results of the investigation into Droughts using time series of coarse resolution daily evapotranspiration produced from the SEBS remote sensing model, on basis of MODIS data. The evapotranspiration will be converted into drought severity using the evapotranspiration deficit index (ETDI). Afterwards the disaggregation to plot scale will be investigated. This disaggregation will be performed as a weighted filtering on basis of crop-coefficient at high resolution. These growth stage of the vegeation (needed for the estimation of the crop coefficients) are estimated on basis of Normalized Difference Vegetation Index (NDVI) using Landsat 5,7 and 8 observations. The final result of the research provides good statistical information about drought resilience and crop health.

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

NASA Astrophysics Data System (ADS)

Linés, Clara; Werner, Micha; Bastiaanssen, Wim

2017-09-01

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

Relating the dynamics of climatological and hydrological droughts in semiarid Botswana

NASA Astrophysics Data System (ADS)

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

2018-06-01

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

A preliminary study on drought events in Peninsular Malaysia

NASA Astrophysics Data System (ADS)

Zin, Wan Zawiah Wan; Nahrawi, Siti Aishah; Jemain, Abdul Aziz; Zahari, Marina

2014-06-01

In this research, the Standard Precipitation Index (SPI) is used to represent the dry condition in Peninsular Malaysia. To do this, data of monthly rainfall from 75 stations in Peninsular Malaysia is used to obtain the SPI values at scale one. From the SPI values, two drought characteristics that are commonly used to represent the dry condition in an area that is the duration and severity of a drought period are identified and their respective values calculated for every station. Spatial mappings are then used to identify areas which are more likely to be affected by longer and more severe drought condition from the results. As the two drought characteristics may be correlated with each other, the joint distribution of severity and duration of dry condition is considered. Bivariate copula model is used and five copula models were tested, namely, the Gumbel-Hougard, Clayton, Frank, Joe and Galambos copulas. The copula model, which best represents the relationship between severity and duration, is determined using Akaike information criterion. The results showed that the Joe and Clayton copulas are well-fitted by close to 60% of the stations under study. Based on the results on the most appropriate copula-based joint distribution for each station, some bivariate probabilistic properties of droughts can then be calculated, which will be continued in future research.

Drought and Fragmentation Impacts on Forest Evapotranspiration in Southwestern Amazonia

NASA Astrophysics Data System (ADS)

Numata, I.; Khand, K.; Kjaersgaard, J.

2017-12-01

We assessed the effects of forest fragmentation and drought on forest evapotranspiration (ET) estimated using the energy balance-based model METRIC with Landsat imagery in Rondônia and Acre in the southwestern Amazon. Forest ET estimates were produced for the dry seasons (June-August) of 2009-2011 thus including the 2010 drought period to quantify its impact by comparing to pre- and post-drought years. Furthermore, we tested forest edge distance, edge density, shape index, and area/edge ratio of forest fragments as fragmentation variables. The 2010 drought year showed the lowest monthly forest ET in August and September in both Rondônia and Acre within the study time period. However, part of the decline of forest ET in Acre during this period appeared to be due to less incoming solar radiation caused by atmospheric contamination from fires in addition to inadequate moisture availability. Lingering impacts of the drought on forest ET were observed in 2011, the post-drought year. Both sites showed lower forest ET in the late dry season in 2011 compared to 2009, the pre-drought year. Among forest fragmentation variables, edge distance presented significant impacts on forest ET in the drought and post-drought years (p<0.05), whereas the other variables were not significant. The magnitude of ET changes along edge distance becomes even greater in the drought year (2010) and the post-drought year (2011) in the month of August.

Drought characteristics and prediction during pasture growing season in Xilingol grassland, northern China

NASA Astrophysics Data System (ADS)

Ma, Qiyun; Zhang, Jiquan; Sun, Caiyun; Zhang, Feng; Wu, Rina; Wu, Lan

2017-06-01

In this paper, spatiotemporal variability of drought in Xilingol grassland during pasture growing season (from April to September) was investigated, using 52 years (1961-2012) of precipitation data recorded at 14 rain gauge stations in the study area. The Standardized Precipitation Index was used to compute the severity of drought. The Mann-Kendall test, the linear trend, and the sequential Mann-Kendall test were applied to standardized precipitation index (SPI) time series. The results indicate that drought has become increasingly serious on the region scale during pasture growing season, and the rate of SPI decreases ranged from -0.112 to -0.013 per decade. As for the MK test, most of the stations, the Z value range is from -1.081 to -0.005 and Kendall's τ varies from -0.104 to -0.024. Meanwhile, drought is increased obviously from the northwest to the southeast region. Meanwhile, the occurrence probability of each severity class, times for reaching different drought class from any drought severity state, and residence times in each drought class have been obtained with Markov chain. Furthermore, the drought severities during pasture growing season in 2013-2016 are predicted depending on the weighted Markov chain. The results may provide a scientific basis for preventing and mitigating drought disaster.

Seasonal and interannual variability of climate and vegetation indices across the Amazon

PubMed Central

Brando, Paulo M.; Goetz, Scott J.; Baccini, Alessandro; Nepstad, Daniel C.; Beck, Pieter S. A.; Christman, Mary C.

2010-01-01

Drought exerts a strong influence on tropical forest metabolism, carbon stocks, and ultimately the flux of carbon to the atmosphere. Satellite-based studies have suggested that Amazon forests green up during droughts because of increased sunlight, whereas field studies have reported increased tree mortality during severe droughts. In an effort to reconcile these apparently conflicting findings, we conducted an analysis of climate data, field measurements, and improved satellite-based measures of forest photosynthetic activity. Wet-season precipitation and plant-available water (PAW) decreased over the Amazon Basin from 1996−2005, and photosynthetically active radiation (PAR) and air dryness (expressed as vapor pressure deficit, VPD) increased from 2002–2005. Using improved enhanced vegetation index (EVI) measurements (2000–2008), we show that gross primary productivity (expressed as EVI) declined with VPD and PAW in regions of sparse canopy cover across a wide range of environments for each year of the study. In densely forested areas, no climatic variable adequately explained the Basin-wide interannual variability of EVI. Based on a site-specific study, we show that monthly EVI was relatively insensitive to leaf area index (LAI) but correlated positively with leaf flushing and PAR measured in the field. These findings suggest that production of new leaves, even when unaccompanied by associated changes in LAI, could play an important role in Basin-wide interannual EVI variability. Because EVI variability was greatest in regions of lower PAW, we hypothesize that drought could increase EVI by synchronizing leaf flushing via its effects on leaf bud development. PMID:20679201

Application of Hydrometeorological Information for Short-term and Long-term Water Resources Management over Ungauged Basin in Korea

NASA Astrophysics Data System (ADS)

Kim, Ji-in; Ryu, Kyongsik; Suh, Ae-sook

2016-04-01

In 2014, three major governmental organizations that are Korea Meteorological Administration (KMA), K-water, and Korea Rural Community Corporation have been established the Hydrometeorological Cooperation Center (HCC) to accomplish more effective water management for scarcely gauged river basins, where data are uncertain or non-consistent. To manage the optimal drought and flood control over the ungauged river, HCC aims to interconnect between weather observations and forecasting information, and hydrological model over sparse regions with limited observations sites in Korean peninsula. In this study, long-term forecasting ensemble models so called Global Seasonal forecast system version 5 (GloSea5): a high-resolution seasonal forecast system, provided by KMA was used in order to produce drought outlook. Glosea5 ensemble model prediction provides predicted drought information for 1 and 3 months ahead with drought index including Standardized Precipitation Index (SPI3) and Palmer Drought Severity Index (PDSI). Also, Global Precipitation Measurement and Global Climate Observation Measurement - Water1 satellites data products are used to estimate rainfall and soil moisture contents over the ungauged region.

Fir Decline and Mortality in the Southern Siberian Mountains

NASA Technical Reports Server (NTRS)

Kharuk, Viacheslav I.; Im, Sergei T.; Petrov, Ilya A.; Dvinskaya, Mariya, L.; Fedotova, Elena V.; Ranson, Kenneth J.

2016-01-01

Increased dieback and mortality of dark needle conifer (DNC) stands (composed of fir (Abies sibirica),Siberian pine (Pinus sibirica) and spruce (Picea obovata)) were documented in Russia during recent decades. Here we analyzed spatial and temporal patterns of fir decline and mortality in the southern Siberian Mountains based on satellite, in situ and dendrochronological data. The studied stands are located within the boundary between DNC taiga to the north and forest-steppe to the south. Fir decline and mortality were observed to originate where topographic features contributed to maximal water-stress risk, i.e., steep (18 deg to 25 deg), convex, south-facing slopes with a shallow well-drained root zone. Fir regeneration survived droughts and increased stem radial growth, while upper canopy trees died. Tree ring width (TRW) growth negatively correlated with vapor pressure deficit (VPD), drought index and occurrence of late frosts, and positively with soil water content. Previous year growth conditions (i.e., drought index, VPD, soil water anomalies) have a high impact on current TRW (r = 0.60 to 0.74). Fir mortality was induced by increased water stress and severe droughts (as a primary factor) in synergy with bark-beetles and fungi attacks (as secondary factors). Dendrochronology data indicated that fir mortality is a periodic process. In a future climate with increased aridity and drought frequency, fir (and Siberian pine) may disappear from portions of its current range (primarily within the boundary with the forest- steppe) and is likely to be replaced by drought-tolerant species such as Pinus sylvestris and Larix sibirica.

Risk assessment of drought disaster in southern China

NASA Astrophysics Data System (ADS)

Wang, Y.

2015-12-01

Abstract: Drought has become an increasing concern in southern China, but the drought risk has not been adequately studied. This study presents a method for the spatial assessment of drought risk in southern China using a conceptual framework that emphasizes the combined role of hazard, vulnerability, and exposure.A drought hazard map was retrieved with a compound index of meteorological drought method in a GIS environment. Normally, a large variation in the disaster-inducing factor implies a high probability of economic/social losses caused by a drought disaster. The map indicated that areas with a higher risk of drought hazard were mainly distributed in mid-east Yunnan and the basins in eastern Sichuan.The vulnerability indices were based on climate factors as well as land use, geomorphological types, soil properties, and drainage density. The water preserving capability of purple calcareous soil in the basins in Sichuan and mid-east Yunnan, and the lateritic red soil in northeastern Guangdong is relatively weak. The main geomorphological features in Guangxi and Guangdong are hills, which leads to a serious expectation of soil and water losses. Thus, the main areas with a high risk of drought vulnerability are mid-east Yunnan and the basins in eastern Sichuan.The exposure indices were based on population density and agricultural production because population and agriculture experience the main impacts of a drought disaster. Higher exposure indices mean higher economic/social losses due to drought disasters. Areas with high exposure indices were mainly distributed in Guangdong and southern Guangxi.The overall risk was then calculated as the product of the hazard, vulnerability, and exposure. The results indicated a higher risk of drought disaster in the basins in eastern Sichuan,, northeastern Yunnan, and northeastern Guangdong. The main factor influencing the risk of a drought disaster was the hazard, but the vulnerability and exposure also played important roles.

Drought frequency in central California since 101 B.C. recordered in giant sequoia tree rings

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

Hughes, M.K.; Brown, P.M.

1992-01-01

Well replicated tree-ring width index chronologies have been developed for giant sequoia at three sites in the Sierra Nevada, California. Extreme low-growth events in these chronologies correspond with regional drought events in the twentieth century in the San Joaquin drainage, in which the giant sequoia sites are located. This relationship is based upon comparison of tree-ring indices with August Palmer Drought Severity Indices for California Climate Division 5. Ring-width indices in the lowest decile from each site were compared. The frequency of low-growth events which occurred at all three sites in the same year is reconstructed from 101 B.C. tomore » A.D. 1988. The inferred frequency of severe drought events changes through time, sometimes suddenly. The period from roughly 1850 to 1950 had one of the lowest frequencies of drought of any one hundred year period in the 2089 year record. The twentieth century so far has had a below-average frequency of extreme droughts. 26 refs., 6 figs., 1 tab.« less

Spatial and temporal trends of drought effects in a heterogeneous semi-arid forest ecosystem

USGS Publications Warehouse

Assal, Timothy J.; Anderson, Patrick J.; Sibold, Jason

2016-01-01

Drought has long been recognized as a driving mechanism in the forests of western North America and drought-induced mortality has been documented across genera in recent years. Given the frequency of these events are expected to increase in the future, understanding patterns of mortality and plant response to severe drought is important to resource managers. Drought can affect the functional, physiological, structural, and demographic properties of forest ecosystems. Remote sensing studies have documented changes in forest properties due to direct and indirect effects of drought; however, few studies have addressed this at local scales needed to characterize highly heterogeneous ecosystems in the forest-shrubland ecotone. We analyzed a 22-year Landsat time series (1985–2012) to determine changes in forest in an area that experienced a relatively dry decade punctuated by two years of extreme drought. We assessed the relationship between several vegetation indices and field measured characteristics (e.g. plant area index and canopy gap fraction) and applied these indices to trend analysis to uncover the location, direction and timing of change. Finally, we assessed the interaction of climate and topography by forest functional type. The Normalized Difference Moisture Index (NDMI), a measure of canopy water content, had the strongest correlation with short-term field measures of plant area index (R2 = 0.64) and canopy gap fraction (R2 = 0.65). Over the entire time period, 25% of the forested area experienced a significant (p-value < 0.05) negative trend in NDMI, compared to less than 10% in a positive trend. Coniferous forests were more likely to be associated with a negative NDMI trend than deciduous forest. Forests on southern aspects were least likely to exhibit a negative trend while north aspects were most prevalent. Field plots with a negative trend had a lower live density, and higher amounts of standing dead and down trees compared to plots with no trend. Our analysis identifies spatially explicit patterns of long-term trends anchored with ground based evidence to highlight areas of forest that are resistant, persistent or vulnerable to severe drought. The results provide a long-term perspective for the resource management of this area and can be applied to similar ecosystems throughout western North America.

Global groundwater sustainability as a function of reliability, resilience and vulnerability

NASA Astrophysics Data System (ADS)

Thomas, B. F.

2017-12-01

The world's largest aquifers are a fundamental source of freshwater used for agricultural irrigation and to meet human water needs. Therefore, their stored volume of groundwater are linked with water security, which becomes more relevant during periods of drought. This work focus on understanding large-scale groundwater changes, where we introduce an approach to evaluate groundwater sustainability at a global scale. We employ a groundwater drought index to assess performance metrics of sustainable use (reliability, resilience, vulnerability) for the largest and most productive global aquifers. Spatiotemporal changes in total water storage are derived from remote sensing observations of gravity anomalies, from which the groundwater drought index is inferred. The performance metrics are then combined into a sustainability index. The results reveal a complex relationship between these sustainable use indicators, while considering monthly variability in groundwater storage. Combining the drought and sustainability indexes, as presented in this work, constitutes a measure for quantifying groundwater sustainability. This framework integrates changes in groundwater resources as a function of human influences and climate changes, thus opening a path to assess both progress towards sustainable use and water security.

High resolution multi-scalar drought indices for Iberia

NASA Astrophysics Data System (ADS)

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

2014-05-01

The Iberian Peninsula has been recurrently affected by drought episodes and by adverse associated effects (Gouveia et al., 2009), ranging from severe water shortages to losses of hydroelectricity production, increasing risk of forest fires, forest decline and triggering processes of land degradation and desertification. Moreover, Iberia corresponds to one of the most sensitive areas to current and future climate change and is nowadays considered a hot spot of climate change with high probability for the increase of extreme events (Giorgi and Lionello, 2008). The spatial and temporal behavior of climatic droughts at different time scales was analyzed using spatially distributed time series of multi-scalar drought indicators, such as the Standardized Precipitation Evapotranspiration Index (SPEI) (Vicente-Serrano et al., 2010). This new climatic drought index is based on the simultaneous use of precipitation and temperature fields with the advantage of combining a multi-scalar character with the capacity to include the effects of temperature variability on drought assessment. Moreover, reanalysis data and the higher resolution hindcasted databases obtained from them are valuable surrogates of the sparse observations and widely used for in-depth characterizations of the present-day climate. Accordingly, this work aims to enhance the knowledge on high resolution drought patterns in Iberian Peninsula, taking advantage of high-resolution (10km) regional MM5 simulations of the recent past (1959-2007) over Iberia. It should be stressed that these high resolution meteorological fields (e.g. temperature, precipitation) have been validated for various purposes (Jerez et al., 2013). A detailed characterization of droughts since the 1960s using the 10 km resolution hidncasted simulation was performed with the aim to explore the conditions favoring drought onset, duration and ending, as well as the subsequent short, medium and long-term impacts affecting the environment and the human resources. The understanding of the present-day underlying mechanisms together with the necessary contextualization within a wider past, is essential to understand future projections, and should lastly rebound on the adequacy of the management decision making. Acknowledgments: This work was partially supported by national funds through FCT (Fundação para a Ciência e a Tecnologia, Portugal) under project QSECA (PTDC/AAG-GLO/4155/2012) Gouveia C., Trigo R.M., DaCamara C.C. (2009) Drought and Vegetation Stress Monitoring in Portugal using Satellite Data, Natural Hazards and Earth System Sciences, 9, 1-11. Giorgi, F. and Lionello, P.; Climate change projections for the Mediterranean region. Global and Planetary Change, 63 (2-3): 90-104, 2008. Vicente-Serrano, Sergio M., Santiago Beguería, Juan I. López-Moreno, 2010: A Multiscalar Drought Index Sensitive to Global Warming: The Standardized Precipitation Evapotranspiration Index. J. Climate, 23, 1696-1718. Jerez, S., R.M. Trigo, S.M. Vicente-Serrano, D. Pozo-Vázquez, R. Lorente-Plazas, J. Lorenzo-Lacruz, F. Santos-Alamillos and J.P. Montávez (2013). The impact of the North Atlantic Oscillation on the renewable energy resources in south-western Europe. Journal of Applied Meteorology and Climatology, DOI 10.1175/JAMC-D-12-0257.1.

Assessing drought risk under climate change in the US Great Plains via evaporative demand from downscaled GCM projections

NASA Astrophysics Data System (ADS)

Dewes, C.; Rangwala, I.; Hobbins, M.; Barsugli, J. J.

2016-12-01

Drought conditions in the US Great Plains occur primarily in response to periods of low precipitation, but they can be exacerbated by enhanced evaporative demand (E0) during periods of elevated temperatures, radiation, advection, and/or decreased humidity. A number of studies project severe to unprecedented drought conditions for this region later in the 21st century. Yet, we have found that methodological choices in the estimation of E0 and the selection of global climate model (GCM) output account for large uncertainties in projections of drought risk. Furthermore, the coarse resolution of GCMs offers little usability for drought risk assessments applied to socio-ecological systems, and users of climate data for that purpose tend to prefer existing downscaled products. Here we derive a physically based estimation of E0 - the FAO56 Penman-Monteith reference evapotranspiration - using driving variables from the Multivariate Adaptive Constructed Analogs (MACA) dataset, which have a spatial resolution of approximately 4 km. We select downscaled outputs from five CMIP5 GCMs, whereby we aim to represent different scenarios for the future of the Great Plains region (e.g. warm/wet, hot/dry, etc.). While this downscaling methodology removes GCM bias relative to a gridded product for historical data (METDATA), we first examine the remaining bias relative to ground (point) estimates of E0. Next we assess whether the downscaled products preserve the variability of their parent GCMs, in both historical and future (RCP8.5) projections. We then use the E0 estimates to compute multi-scale time series of drought indices such as the Evaporative Demand Drought Index (EDDI) and the Standardized Precipitation-Evaporation Index (SPEI) over the Great Plains region. We also attribute variability and drought anomalies to each of the driving parameters, to tease out the influence of specific model biases and evaluate geographical nuances of E0 drivers. Aside from improved understanding of plausible future drought conditions at higher spatial resolutions, our findings should offer insights on the reliability of downscaled projections for drought risk assessment in socio-ecological applications.

Drought propagation in the Paraná Basin, Brazil: from rainfall deficits to impacts on reservoir storage

NASA Astrophysics Data System (ADS)

Melo, D. D.; Wendland, E.

2017-12-01

The sensibility and resilience of hydrologic systems to climate changes are crucial for estimating potential impacts of droughts, responsible for major economic and human losses globally. Understanding how droughts propagate is a key element to develop a predictive understanding for future management and mitigation strategies. In this context, this study investigated the drought propagation in the Paraná Basin (PB), Southeast Brazil, a major hydroelectricity producing region with 32 % (60 million people) of the country's population. Reservoir storage (RESS), river discharge (Q) and rainfall (P) data were used to assess the linkages between meteorological and hydrological droughts, characterized by the Standard Precipitation Index (SPI) and Streamflow Drought Index (SDI), respectively. The data are from 37 sub-basins within the PB, consisting of contributing areas of 37 reservoirs (250 km3 of stored water) within the PB for the period between 1995 and 2015. The response time (RT) of the hydrologic system to droughts, given as the time lag between P, Q and RESS, was quantified using a non-parametric statistical method that combines cumulative sums and Bootstrap resampling technique. Based on our results, the RTs of the hydrologic system of the PB varies from 0 to 6 months, depending on a number of aspects: lithology, topography, dam operation, etc. Linkages between SPI and SDI indicated that the anthropogenic control (dam operation) plays an important role in buffering drought impacts to downstream sub-basins: SDI decreased from upstream to downstream despite similar SPI values over the whole area. Comparisons between sub-basins, with variable drainage sizes (5,000 - 50,000 km2), confirmed the benefice of upstream reservoirs in reducing hydrological droughts. For example, the RT for a 4,800 km2 basin was 6 months between P and Q and 9 months between Q and RESS, under anthropogenic control. Conversely, the RT to precipitation for a reservoir subjected to natural controls only (no major human influence on storage and routing) was less than 1 month for both Q and RESS. This study underscores the importance of the reservoirs in the Paraná basin in reducing drought impacts on water supply and energy generation.

An approach to drought data web-dissemination

NASA Astrophysics Data System (ADS)

Angeluccetti, Irene; Perez, Francesca; Balbo, Simone; Cámaro, Walther; Boccardo, Piero

2017-04-01

Drought data dissemination has always been a challenge for the scientific community. Firstly, a variety of widely known datasets is currently being used to describe different aspects of this same phenomenon. Secondly, new indexes are constantly being produced by scientists trying to better capture drought events. The present work aims at presenting how the drought monitoring communication issue was addressed by the ITHACA team. The ITHACA drought monitoring system makes use of two indicators: the Standardized Precipitation Index (SPI) and the Seasonal Small Integral Deviation (SSID). The first one is obtained considering the 3-months cumulating interval of the rainfall derived from the TRMM dataset; the second one is the percent deviation from the historical average value of the integral of the NDVI function describing the vegetation season. The SPI and the SSID are 30 and 5 km gridded respectively. The whole time-series of these two indicators (since year 2000 onwards), covering the whole Africa, are published by a WebGIS platform (http://drought.ithacaweb.org). On the one hand, although the SPI has been used for decades in different contexts and little explanation is due when presenting this indicator to an audience with a scientific background, the WebGIS platform shows a guide for its correct interpretation. On the other hand, being the SSID not commonly used in the field of vegetation analysis, the guide shown on the WebGIS platform is essential for the visitor to understand the data. Recently a new index has been created in order to synthesize, for a non-expert audience, the information provided by the indicators. It is aggregated per second order administrative levels and is calculated as follows: (i) a meteorological drought warning is issued when negative SPI and no vegetative season is detected (a blue palette is used); (ii) a warning value is assigned if SSID, SPI, or both, are negative (amber to brown palette is used) i.e., where the vegetative season is ongoing and the SSID is negative, a negative SPI value entails an agricultural drought warning, while a positive SPI implies a vegetation stress warning; (iv) a meteorological drought warning is issued when negative SPI during the vegetation season is detected but vegetation stress effects are not (i.e. positive SSID). The latest available Drought Warning Index is also published on the mentioned WebGIS platform. The index is stored in a database table: a single value is calculated for each administrative level. A table view on the database contains fields describing the geometry of the administrative level polygons and the respective index; this table view is published as a WMS service, by associating the symbology previously described. The WMS service is then captured in order to generate a live map with a series of basic WebGIS functionalities. The integrated index is undoubtedly useful for a non-expert user to understand immediately if a particular region is subject to a drought stress. However, the simplification introduces uncertainty as it implies several assumptions that couldn't be verified at a continental scale.

Assessment of Water Sustainability Index Using Reliability-Resilience-Vulnerability Criteria Considering Climatic Variation over India

NASA Astrophysics Data System (ADS)

Lakshmi, V.; Mondal, A.; Kundu, S.

2016-12-01

Abstract:Precipitation can be considered as a key factor in Water Resources Sustainability (WRS). In India, WRS varies with widely varying distribution of precipitation. The economy of the India is based on agricultural production which mainly depends on rainfall. The main focus of the paper is assessment of Water Sustainability based on Standardized Precipitation Index (SPI) method for evaluating drought and non-drought conditionsin India using a precipitation data of a long time period (1871-2014). The study area has been divided into thirty sub-regions on the basis homogeneity pattern of rainfall distribution. The performance criteria such as, Reliability, Resilience, Vulnerability and Relative Vulnerability (RV) have been applied in this study. The ranges of water sustainably (WS), vulnerability, relative vulnerability and drought resilience are 0.26 to 0.67, 0.52 to 1.06, 0.22 to 0.61 and 0.72 to 1 respectively. Specifically, WS of Gangetic West Bengal, Naga-Mani-Mizo-trip, Konkan-Goa, Chattisgarh and Kerala are less (0.26, 0.31, 0.35, 0.38 and 0.38 respectively) while Punjab, Marathwada, West Rajasthan and Vidarbha are more (0.57, 0.60, 0.67 and 0.57 respectively).Finally, WS and RV have shown negative correlation (R2=0.86) while WS and drought resilience have shown positive correlation (R2=0.60). The results have clearly illustrated a scenario of entire India, which can be helpful in agricultural management in future. Key Words: Sustainability, SPI, Reliability, Resilience, Vulnerability

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Comparing the Palmer Drought Index and the Standardized Precipitation Index for Zagreb-Gric Observatory

NASA Astrophysics Data System (ADS)

Pandzic, Kreso

2014-05-01

Conventional Palmer Drought Index (PDSI) and recent Standardized Precipitation Index (SPI) are compared for Zagreb-Gric weather station. Historical time series of PDSI and SPI are compared. For that purpose monthly precipitation, air temperature and air humidity data for Zagreb-Gric Observatory and period 1862-2010 are used. The results indicate that SPI is simpler for interpretation than PDI. On the other side, lack of temperature within SPI, make impossible use of it on climate change applications. Further development of both indices is required. Possible applications of them in irrigation scheduling system is considered as well for drought risk assessment. In addition, a comparison of PDSI and SPI for the periods from 1 to 24 months indicate the best agreement between PDSI and SPI for the periods from 6 to 12 months.

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

NASA Astrophysics Data System (ADS)

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

2009-12-01

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

Application of Multi-Model CMIP5 Analysis in Future Drought Adaptation Strategies

NASA Astrophysics Data System (ADS)

Casey, M.; Luo, L.; Lang, Y.

2014-12-01

Drought influences the efficacy of numerous natural and artificial systems including species diversity, agriculture, and infrastructure. Global climate change raises concerns that extend well beyond atmospheric and hydrological disciplines - as climate changes with time, the need for system adaptation becomes apparent. Drought, as a natural phenomenon, is typically defined relative to the climate in which it occurs. Typically a 30-year reference time frame (RTF) is used to determine the severity of a drought event. This study investigates the projected future droughts over North America with different RTFs. Confidence in future hydroclimate projection is characterized by the agreement of long term (2005-2100) multi-model precipitation (P) and temperature (T) projections within the Coupled model Intercomparison Project Phase 5 (CMIP5). Drought severity and the propensity of extreme conditions are measured by the multi-scalar, probabilistic, RTF-based Standard Precipitation Index (SPI) and Standard Precipitation Evapotranspiration Index (SPEI). SPI considers only P while SPEI incorporates Evapotranspiration (E) via T; comparing the two reveals the role of temperature change in future hydroclimate change. Future hydroclimate conditions, hydroclimate extremity, and CMIP5 model agreement are assessed for each Representative Concentration Pathway (RCP 2.6, 4.5, 6.0, 8.5) in regions throughout North America for the entire year and for the boreal seasons. In addition, multiple time scales of SPI and SPEI are calculated to characterize drought at time scales ranging from short to long term. The study explores a simple, standardized method for considering adaptation in future drought assessment, which provides a novel perspective to incorporate adaptation with climate change. The result of the analysis is a multi-dimension, probabilistic summary of the hydrological (P, E) environment a natural or artificial system must adapt to over time. Studies similar to this with specified criteria (SPI/SPEI value, time scale, RCP, etc.) can provide professionals in a variety of disciplines with necessary climatic insight to develop adaptation strategies.

Trends and Tipping Points of Drought-induced Tree Mortality

NASA Astrophysics Data System (ADS)

Huang, K.; Yi, C.; Wu, D.; Zhou, T.; Zhao, X.; Blanford, W. J.; Wei, S.; Wu, H.; Du, L.

2014-12-01

Drought-induced tree mortality worldwide has been recently reported in a review of the literature by Allen et al. (2010). However, a quantitative relationship between widespread loss of forest from mortality and drought is still a key knowledge gap. Specifically, the field lacks quantitative knowledge of tipping point in trees when coping with water stress, which inhibits the assessments of how climate change affects the forest ecosystem. We investigate the statistical relationships for different (seven) conifer species between Ring Width Index (RWI) and Standardized Precipitation Evapotranspiration Index (SPEI), based on 411 chronologies from the International Tree-Ring Data Bank across 11 states of the western United States. We found robust species-specific relationships between RWI and SPEI for all seven conifer species at dry condition. The regression models show that the RWI decreases with SPEI decreasing (drying) and more than 76% variation of tree growth (RWI) can be explained by the drought index (SPEI). However, when soil water is sufficient (i.e., SPEI>SPEIu), soil water is no longer a restrictive factor for tree growth and, therefore, the RWI shows a weak correlation with SPEI. Based on the statistical models, we derived the tipping point of SPEI (SPEItp) where the RWI equals 0, which means the carbon efflux by tree respiration equals carbon influx by tree photosynthesis. When the severity of drought exceeds this tipping point(i.e. SPEI

Evaluation of drought using SPEI drought class transitions and log-linear models for different agro-ecological regions of India

NASA Astrophysics Data System (ADS)

Alam, N. M.; Sharma, G. C.; Moreira, Elsa; Jana, C.; Mishra, P. K.; Sharma, N. K.; Mandal, D.

2017-08-01

Markov chain and 3-dimensional log-linear models were attempted to model drought class transitions derived from the newly developed drought index the Standardized Precipitation Evapotranspiration Index (SPEI) at a 12 month time scale for six major drought prone areas of India. Log-linear modelling approach has been used to investigate differences relative to drought class transitions using SPEI-12 time series derived form 48 yeas monthly rainfall and temperature data. In this study, the probabilities of drought class transition, the mean residence time, the 1, 2 or 3 months ahead prediction of average transition time between drought classes and the drought severity class have been derived. Seasonality of precipitation has been derived for non-homogeneous Markov chains which could be used to explain the effect of the potential retreat of drought. Quasi-association and Quasi-symmetry log-linear models have been fitted to the drought class transitions derived from SPEI-12 time series. The estimates of odds along with their confidence intervals were obtained to explain the progression of drought and estimation of drought class transition probabilities. For initial months as the drought severity increases the calculated odds shows lower value and the odds decreases for the succeeding months. This indicates that the ratio of expected frequencies of occurrence of transition from drought class to the non-drought class decreases as compared to transition to any drought class when the drought severity of the present class increases. From 3-dimensional log-linear model it is clear that during the last 24 years the drought probability has increased for almost all the six regions. The findings from the present study will immensely help to assess the impact of drought on the gross primary production and to develop future contingent planning in similar regions worldwide.

Climatic Droughts and the Impacts on Crop Yields in Northern India during the Past Century

NASA Astrophysics Data System (ADS)

Ge, Y.; Cai, X.; Zhu, T.

2014-12-01

Drought has become an increasingly severe threat to water and food security recently. This study presents a novel method to calculate the return period of drought, considering drought as event characterized by expected drought inter-arrival time, duration, severity and peak intensity. Recently, Copula distribution, a multivariable probability distribution, is used to deal with strongly correlated variables in analyzing complex hydrologic phenomenon. This study assesses drought conditions in Northern India, including 8 sites, in the past century using Palmer Drought Severity Index (PDSI) from two latest datasets, Dai (2011, 2013) and Sheffield et al. (2012), which concluded conflicting results about global average drought trend. Our results include the change of the severity, intensity and duration of drought events during the past century and the impact of the drought condition on crop yields in the region. It is found that drought variables are highly correlated, thus copulas joint distribution enables the estimation of multi-variate return period. Based on Dai's dataset from 1900 to 2012, for a fixed drought return period the severity and duration is lower for the period before1955 in sites close to the Indus basin (site 1) or off the coast of the Indian Ocean (Bay of Bengal) (site 8), while they are higher for the period after 1955 in other inland sites (sites 3-7), (e.g., severity in Fig.1). Projections based on two models (IPCC AR4 and AR5) in Dai (2011, 2013) suggested less severity and shorter duration in longer-year drought (e.g., 100-year drought), but larger in shorter-year drought (e.g., 2-year drought). Drought could bring nonlinear responses and unexpected losses in agriculture system, thus prediction and management are essential. Therefore, in the years with extreme drought conditions, impact assessment of drought on crop yield of corn, barley, wheat and sorghum will be also conducted through correlating crop yields with drought conditions during corresponding growing seasons. A. Dai, J. Geophys. Res., 116, D12115 (2011).A. Dai, Nature Climate Change, 3, 52-58 (2013). J. Sheffield, E.F. Wood, M. L. Roderick, Nature, 491, 435-438 (2012) Fig. 1 Return period for severity from 1900 to 1954 (green), from 1955 to 2012 (red), and from 2013 to 2099 (black for AR4, blue for AR5), respectively for 8 sites.

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

NASA Astrophysics Data System (ADS)

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

2017-03-01

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

Rainfall characterisation by application of standardised precipitation index (SPI) in Peninsular Malaysia

NASA Astrophysics Data System (ADS)

Yusof, Fadhilah; Hui-Mean, Foo; Suhaila, Jamaludin; Yusop, Zulkifli; Ching-Yee, Kong

2014-02-01

The interpretations of trend behaviour for dry and wet events are analysed in order to verify the dryness and wetness episodes. The fitting distribution of rainfall is computed to classify the dry and wet events by applying the standardised precipitation index (SPI). The rainfall amount for each station is categorised into seven categories, namely extremely wet, severely wet, moderately wet, near normal, moderately dry, severely dry and extremely dry. The computation of the SPI is based on the monsoon periods, which include the northeast monsoon, southwest monsoon and inter-monsoon. The trends of the dry and wet periods were then detected using the Mann-Kendall trend test and the results indicate that the major parts of Peninsular Malaysia are characterised by increasing droughts rather than wet events. The annual trends of drought and wet events of the randomly selected stations from each region also yield similar results. Hence, the northwest and southwest regions are predicted to have a higher probability of drought occurrence during a dry event and not much rain during the wet event. The east and west regions, on the other hand, are going through a significant upward trend that implies lower rainfall during the drought episodes and heavy rainfall during the wet events.

Quantitative trait locus mapping under irrigated and drought treatments based on a novel genetic linkage map in mungbean (Vigna radiata L.).

PubMed

Liu, Changyou; Wu, Jing; Wang, Lanfen; Fan, Baojie; Cao, Zhimin; Su, Qiuzhu; Zhang, Zhixiao; Wang, Yan; Tian, Jing; Wang, Shumin

2017-11-01

A novel genetic linkage map was constructed using SSR markers and stable QTLs were identified for six drought tolerance related-traits using single-environment analysis under irrigation and drought treatments. Mungbean (Vigna radiata L.) is one of the most important leguminous food crops. However, mungbean production is seriously constrained by drought. Isolation of drought-responsive genetic elements and marker-assisted selection breeding will benefit from the detection of quantitative trait locus (QTLs) for traits related to drought tolerance. In this study, we developed a full-coverage genetic linkage map based on simple sequence repeat (SSR) markers using a recombinant inbred line (RIL) population derived from an intra-specific cross between two drought-resistant varieties. This novel map was anchored with 313 markers. The total map length was 1010.18 cM across 11 linkage groups, covering the entire genome of mungbean with a saturation of one marker every 3.23 cM. We subsequently detected 58 QTLs for plant height (PH), maximum leaf area (MLA), biomass (BM), relative water content, days to first flowering, and seed yield (Yield) and 5 for the drought tolerance index of 3 traits in irrigated and drought environments at 2 locations. Thirty-eight of these QTLs were consistently detected two or more times at similar linkage positions. Notably, qPH5A and qMLA2A were consistently identified in marker intervals from GMES5773 to MUS128 in LG05 and from Mchr11-34 to the HAAS_VR_1812 region in LG02 in four environments, contributing 6.40-20.06% and 6.97-7.94% of the observed phenotypic variation, respectively. None of these QTLs shared loci with previously identified drought-related loci from mungbean. The results of these analyses might facilitate the isolation of drought-related genes and help to clarify the mechanism of drought tolerance in mungbean.

Analysis of extreme hydrological phenomena in southern Italy (Calabria region)

NASA Astrophysics Data System (ADS)

Caloiero, Tommaso; Aceto, Luigi; Aurora Pasqua, A.; Petrucci, Olga

2017-04-01

Calabria (southern Italy) is a region exposed to the effects of contrasting climatic and hydrological phenomena. In fact, due to its oblong shape, to its position in the middle of the Mediterranean Basin, and for its mountainous nature, Calabria shows a high spatial variability of the climatic features and of related phenomena such as floods and drought. The present paper is based on the historical database ASICal (Historically flooded areas in Calabria), a catalogue of effects of floods and rain-related landslides that occurred in the region since the XIX Century. The catalogue has been built using the typical historical data sources as chronicles, diaries, historical books, local and regional agencies, press archives, scientific papers, and documents of civil protection offices. From these sources, we selected information on damage caused by rain related phenomena at a municipal scale and chronologically sorted by year, month and day. The analysis of the entire catalogue allows highlighting the regional Damaging Hydrogeological Events (DHE), defined as periods of intense rain causing damage on regional sectors conventionally selected as larger than 30% of the entire regional territory. For each event, as a measure of the magnitude of rainfall, the return period of the daily rainfall recorded during the event has been evaluated. In addition, we recently carried out a similar historical research to identify the main drought events affecting the region. In this case, due to the spatial and temporal characteristics of drought, data are collected both at municipal and regional scale, and the temporal scale is generally monthly or annual. For each event, we used as climatic descriptors a drought index for monitoring drought phenomena. Among drought indices, we used the Standardized Precipitation Index (SPI) which can be considered the most robust and effective, since it can be calculated for different time-scales and can be used to analyse different drought categories. Moreover, the SPI is easier to calculate than complex indices, as it is based on precipitation alone, and allows comparing drought conditions among different periods and regions. Both the series have been analysed jointly, in order to obtain the general trend of extreme rain and drought, characterised by mean of descriptive climatic features and damage caused. The results supply a glance in the past climatic history of the region that can be used to project to future and be prepared for ongoing changes related to climate changes. In fact, the identification of the most floods and drought prone areas can be useful for both civil protection mitigation strategies and water resources management (water used for home, industrial, and agricultural purposes).

Remotely-sensed detection of effects of extreme droughts on gross primary production

PubMed Central

Vicca, Sara; Balzarolo, Manuela; Filella, Iolanda; Granier, André; Herbst, Mathias; Knohl, Alexander; Longdoz, Bernard; Mund, Martina; Nagy, Zoltan; Pintér, Krisztina; Rambal, Serge; Verbesselt, Jan; Verger, Aleixandre; Zeileis, Achim; Zhang, Chao; Peñuelas, Josep

2016-01-01

Severe droughts strongly impact photosynthesis (GPP), and satellite imagery has yet to demonstrate its ability to detect drought effects. Especially changes in vegetation functioning when vegetation state remains unaltered (no browning or defoliation) pose a challenge to satellite-derived indicators. We evaluated the performance of different satellite indicators to detect strong drought effects on GPP in a beech forest in France (Hesse), where vegetation state remained largely unaffected while GPP decreased substantially. We compared the results with three additional sites: a Mediterranean holm oak forest (Puéchabon), a temperate beech forest (Hainich), and a semi-arid grassland (Bugacpuszta). In Hesse, a three-year reduction in GPP following drought was detected only by the Enhanced Vegetation Index (EVI). The Photochemical Reflectance Index (PRI) also detected this drought effect, but only after normalization for absorbed light. In Puéchabon normalized PRI outperformed the other indicators, while the short-term drought effect in Hainich was not detected by any tested indicator. In contrast, most indicators, but not PRI, captured the drought effects in Bugacpuszta. Hence, PRI improved detection of drought effects on GPP in forests and we propose that PRI normalized for absorbed light is considered in future algorithms to estimate GPP from space. PMID:27301671

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

PubMed

Maes, W H; Steppe, K

2012-08-01

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

Asian droughts in the last millennium: a search for robust impacts of Pacific Ocean surface temperature variabilities

NASA Astrophysics Data System (ADS)

Yu, Entao; King, Martin P.; Sobolowski, Stefan; Otterå, Odd Helge; Gao, Yongqi

2018-06-01

This study investigates the robustness of hydroclimate impacts in Asia due to major drivers of climate variability in the Pacific Ocean, namely the El Niño-Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO). Composite analyses are carried out on a tree ring-based Palmer Drought Severity Index as well as on a long coupled global climate model control experiment. El Niño (La Niña) has a robust impact on wet (dry) conditions in West Asia and dry (wet) conditions in South Asia. For the PDO, impacts are found throughout the Asia domain. However, identifying the robust signals due to PDO from these analyses is more challenging due to the limited lengths of the data. Results indicate that West Asia (South and Southeast Asia) experiences wet (dry) conditions during periods of positive PDO. For East Asia, there is indication that positive (negative) PDO is associated with wet (dry) conditions around and southward of 30°N and dry (wet) conditions north of this latitude. This result is consistent with the current understanding of the role of PDO in the "southern-flood northern-drought" phenomenon in China. We suggest that specific extreme events or periods have regional impacts with strong intensities that cannot be fully explained through the composite analysis of ENSO, PDO, or any combination thereof. Two such examples are shown to illustrate this: the Strange Parallel Drought (1756-1768 CE) and the Great Drought (1876-1878 CE). Additionally, during these climate events, ENSO and PDO can be in phases which are not consistent with the required phases of these drivers that explain the concurrent drought and pluvial conditions in Asia. Therefore, not all historical drought and pluvial events in Northeast Asia and northern China can be related back to ENSO or PDO. Finally, we also examine the dynamical characteristics of the reported hydroclimatic impacts in the global climate model experiment. There is moisture transport into (out of) regions that exhibit wet (dry) conditions in a manner consistent with the various ENSO and PDO composites, thereby providing physical explanation of the index-based results.

Spatial variability of NDVI at different seasons in the Community of Madrid (Spain)

NASA Astrophysics Data System (ADS)

Sotoca, Juan J. Martin; Saa-Requejo, Antonio; Borondo, Javier; Tarquis, Ana M.

2015-04-01

Agricultural drought quantification is one of the most important tasks in the characterization process of this natural hazard and its implications in crop insurance. Recently, several vegetation indexes based on remote-sensing data (VI) has been applied to quantify it (Dalezios et al, 2012). VIs are obtained combining several frequency bands that represent the relationship between photosynthesis and absorbed/reflected radiation. The most widely used VI is the Normalized Difference Vegetation Index (NDVI). It is based on the principle that healthy vegetation mainly absorbs visible light and reflects the near-infrared frequency band. Drought can be highly localized, and several authors have recognized the critical role of soil moisture and its spatial variability in agricultural losses (Anderson et al., 2011). Therefore, it is important to delimit locations within a homogeneous area that will share main NDVI statistics and in which the same threshold value can be applied to define drought event. In order to do so, we have applied for the first time in this context the method of singularity maps (Cheng and Agterberg, 1996) commonly used in localization of mineral deposits. The NDVI singularity maps calculated in each season through 2011/2012 are showed and discussed (Martín-Sotoca, 2014). References Anderson, M:C:, C. R. Hain, B. Wardlow, J. R. Mecikalski and W. P. Kustas (2011) Evaluation of drought indices based on thermal remote sensing of evapotranspiration over the continental United States. J. Climate, 24, 2025-2044. Dalezios, N.R., A. Blanta, N.V. Spyropoulos and A.M. Tarquis (2012) Risk identification of agricultural drought for sustainable Agroecosystems. Nat. Hazards Earth Syst. Sci., 14, 2435-2448. Cheng, Q. and F.P. Agterberg (1996) Multifractal modeling and spatial statistics. Math. Geol., 28, 1-16. Martín-Sotoca, J.J. (2014) Estructura Espacial de la Sequía en Pastos y sus Aplicaciones en el Seguro Agrario. Master Thesis, UPM (In Spanish). Acknowledgements First author acknowledges the Research Grant obtained from CEIGRAM in 2014

Natural variability of the Keetch-Byram Drought Index in the Hawaiian Islands

Treesearch

Klaus Dolling; Pao-Shin Chu; Francis Fujioka

2009-01-01

The Hawaiian Islands experience damaging wildfires on a yearly basis. Soil moisture or lack thereof influences the amount and flammability of vegetation. Incorporating daily maximum temperatures and daily rainfall amounts, the Keetch–Byram Drought Index (KBDI) estimates the amount of soil moisture by tracking daily maximum temperatures and rainfall. A previous study...

Effect of water stress on total biomass, tuber yield, harvest index and water use efficiency in Jerusalem artichoke

USDA-ARS?s Scientific Manuscript database

The objectives of this study were to determine the effect of drought on tuber yield, total biomass, harvest index, water use efficiency of tuber yield (WUEt) and water use efficiency of biomass (WUEb), and to evaluate the differential responses of Jerusalem artichoke (JA) varieties under drought str...

Climate signals in a multispecies tree-ring network from central and southern Italy and reconstruction of the late summer temperatures since the early 1700s

NASA Astrophysics Data System (ADS)

Leonelli, Giovanni; Coppola, Anna; Salvatore, Maria Cristina; Baroni, Carlo; Battipaglia, Giovanna; Gentilesca, Tiziana; Ripullone, Francesco; Borghetti, Marco; Conte, Emanuele; Tognetti, Roberto; Marchetti, Marco; Lombardi, Fabio; Brunetti, Michele; Maugeri, Maurizio; Pelfini, Manuela; Cherubini, Paolo; Provenzale, Antonello; Maggi, Valter

2017-11-01

A first assessment of the main climatic drivers that modulate the tree-ring width (RW) and maximum latewood density (MXD) along the Italian Peninsula and northeastern Sicily was performed using 27 forest sites, which include conifers (RW and MXD) and broadleaves (only RW). Tree-ring data were compared using the correlation analysis of the monthly and seasonal variables of temperature, precipitation and standardized precipitation index (SPI, used to characterize meteorological droughts) against each species-specific site chronology and against the highly sensitive to climate (HSTC) chronologies (based on selected indexed individual series). We find that climate signals in conifer MXD are stronger and more stable over time than those in conifer and broadleaf RW. In particular, conifer MXD variability is directly influenced by the late summer (August, September) temperature and is inversely influenced by the summer precipitation and droughts (SPI at a timescale of 3 months). The MXD sensitivity to August-September (AS) temperature and to summer drought is mainly driven by the latitudinal gradient of summer precipitation amounts, with sites in the northern Apennines showing stronger climate signals than sites in the south. Conifer RW is influenced by the temperature and drought of the previous summer, whereas broadleaf RW is more influenced by summer precipitation and drought of the current growing season. The reconstruction of the late summer temperatures for the Italian Peninsula for the past 300 years, based on the HSTC chronology of conifer MXD, shows a stable model performance that underlines periods of climatic cooling (and likely also wetter conditions) in 1699, 1740, 1814, 1914 and 1938, and follows well the variability of the instrumental record and of other tree-ring-based reconstructions in the region. Considering a 20-year low-pass-filtered series, the reconstructed temperature record consistently deviates < 1 °C from the instrumental record. This divergence may also be due to the precipitation patterns and drought stresses that influence the tree-ring MXD at our study sites. The reconstructed late summer temperature variability is also linked to summer drought conditions and it is valid for the west-east oriented region including Sardinia, Sicily, the Italian Peninsula and the western Balkan area along the Adriatic coast.

Predicting East African spring droughts using Pacific and Indian Ocean sea surface temperature indices

USGS Publications Warehouse

Funk, Christopher C.; Hoell, Andrew; Shukla, Shraddhanand; Blade, Ileana; Liebmann, Brant; Roberts, Jason B.; Robertson, Franklin R.

2014-01-01

In southern Ethiopia, Eastern Kenya, and southern Somalia poor boreal spring rains in 1999, 2000, 2004, 2007, 2008, 2009 and 2011 contributed to severe food insecurity and high levels of malnutrition. Predicting rainfall deficits in this region on seasonal and decadal time frames can help decision makers support disaster risk reduction while guiding climate-smart adaptation and agricultural development. Building on recent research that links more frequent droughts to a stronger Walker Circulation, warming in the Indo-Pacific warm pool, and an increased western Pacific sea surface temperature (SST) gradient, we explore the dominant modes of East African rainfall variability, links between these modes and sea surface temperatures, and a simple index-based monitoring-prediction system suitable for drought early warning.

Climatic factors driving vegetation declines in the 2005 and 2010 Amazon droughts

PubMed Central

Zhao, Wenqian; Zhao, Xiang; Zhou, Tao; Wu, Donghai; Tang, Bijian; Wei, Hong

2017-01-01

Along with global climate change, the occurrence of extreme droughts in recent years has had a serious impact on the Amazon region. Current studies on the driving factors of the 2005 and 2010 Amazon droughts has focused on the influence of precipitation, whereas the impacts of temperature and radiation have received less attention. This study aims to explore the climate-driven factors of Amazonian vegetation decline during the extreme droughts using vegetation index, precipitation, temperature and radiation datasets. First, time-lag effects of Amazonian vegetation responses to precipitation, radiation and temperature were analyzed. Then, a multiple linear regression model was established to estimate the contributions of climatic factors to vegetation greenness, from which the dominant climate-driving factors were determined. Finally, the climate-driven factors of Amazonian vegetation greenness decline during the 2005 and 2010 extreme droughts were explored. The results showed that (i) in the Amazon vegetation greenness responded to precipitation, radiation and temperature, with apparent time lags for most averaging interval periods associated with vegetation index responses of 0–4, 0–9 and 0–6 months, respectively; (ii) on average, the three climatic factors without time lags explained 27.28±21.73% (mean±1 SD) of vegetation index variation in the Amazon basin, and this value increased by 12.22% and reached 39.50±27.85% when time lags were considered; (iii) vegetation greenness in this region in non-drought years was primarily affected by precipitation and shortwave radiation, and these two factors altogether accounted for 93.47% of the total explanation; and (iv) in the common epicenter of the two droughts, pixels with a significant variation in precipitation, radiation and temperature accounted for 36.68%, 40.07% and 10.40%, respectively, of all pixels showing a significant decrease in vegetation index in 2005, and 15.69%, 2.01% and 45.25% in 2010, respectively. Overall, vegetation greenness declines during the 2005 and 2010 extreme droughts were adversely influenced by precipitation, radiation and temperature; this study provides evidence of the influence of multiple climatic factors on vegetation during the 2005 and 2010 Amazon droughts. PMID:28426691

Climatic factors driving vegetation declines in the 2005 and 2010 Amazon droughts.

PubMed

Zhao, Wenqian; Zhao, Xiang; Zhou, Tao; Wu, Donghai; Tang, Bijian; Wei, Hong

2017-01-01

Along with global climate change, the occurrence of extreme droughts in recent years has had a serious impact on the Amazon region. Current studies on the driving factors of the 2005 and 2010 Amazon droughts has focused on the influence of precipitation, whereas the impacts of temperature and radiation have received less attention. This study aims to explore the climate-driven factors of Amazonian vegetation decline during the extreme droughts using vegetation index, precipitation, temperature and radiation datasets. First, time-lag effects of Amazonian vegetation responses to precipitation, radiation and temperature were analyzed. Then, a multiple linear regression model was established to estimate the contributions of climatic factors to vegetation greenness, from which the dominant climate-driving factors were determined. Finally, the climate-driven factors of Amazonian vegetation greenness decline during the 2005 and 2010 extreme droughts were explored. The results showed that (i) in the Amazon vegetation greenness responded to precipitation, radiation and temperature, with apparent time lags for most averaging interval periods associated with vegetation index responses of 0-4, 0-9 and 0-6 months, respectively; (ii) on average, the three climatic factors without time lags explained 27.28±21.73% (mean±1 SD) of vegetation index variation in the Amazon basin, and this value increased by 12.22% and reached 39.50±27.85% when time lags were considered; (iii) vegetation greenness in this region in non-drought years was primarily affected by precipitation and shortwave radiation, and these two factors altogether accounted for 93.47% of the total explanation; and (iv) in the common epicenter of the two droughts, pixels with a significant variation in precipitation, radiation and temperature accounted for 36.68%, 40.07% and 10.40%, respectively, of all pixels showing a significant decrease in vegetation index in 2005, and 15.69%, 2.01% and 45.25% in 2010, respectively. Overall, vegetation greenness declines during the 2005 and 2010 extreme droughts were adversely influenced by precipitation, radiation and temperature; this study provides evidence of the influence of multiple climatic factors on vegetation during the 2005 and 2010 Amazon droughts.

Tree-ring-based drought reconstruction in the Iberian Range (east of Spain) since 1694

NASA Astrophysics Data System (ADS)

Tejedor, Ernesto; de Luis, Martín; Cuadrat, José María; Esper, Jan; Saz, Miguel Ángel

2016-03-01

Droughts are a recurrent phenomenon in the Mediterranean basin with negative consequences for society, economic activities, and natural systems. Nevertheless, the study of drought recurrence and severity in Spain has been limited so far due to the relatively short instrumental period. In this work, we present a reconstruction of the standardized precipitation index (SPI) for the Iberian Range. Growth variations and climatic signals within the network are assessed developing a correlation matrix and the data combined to a single chronology integrating 336 samples from 169 trees of five different pine species distributed throughout the province of Teruel. The new chronology, calibrated against regional instrumental climatic data, shows a high and stable correlation with the July SPI integrating moisture conditions over 12 months forming the basis for a 318-year drought reconstruction. The climate signal contained in this reconstruction is highly significant ( p < 0.05) and spatially robust over the interior areas of Spain located above 1000 meters above sea level (masl). According to our SPI reconstruction, seven substantially dry and five wet periods are identified since the late seventeenth century considering ≥±1.76 standard deviations. Besides these, 36 drought and 28 pluvial years were identified. Some of these years, such as 1725, 1741, 1803, and 1879, are also revealed in other drought reconstructions in Romania and Turkey, suggesting that coherent larger-scale synoptic patterns drove these extreme deviations. Since regional drought deviations are also retained in historical documents, the tree-ring-based reconstruction presented here will allow us to cross-validate drought frequency and magnitude in a highly vulnerable region.

Tree-ring-based drought reconstruction in the Iberian Range (east of Spain) since 1694.

PubMed

Tejedor, Ernesto; de Luis, Martín; Cuadrat, José María; Esper, Jan; Saz, Miguel Ángel

2016-03-01

Droughts are a recurrent phenomenon in the Mediterranean basin with negative consequences for society, economic activities, and natural systems. Nevertheless, the study of drought recurrence and severity in Spain has been limited so far due to the relatively short instrumental period. In this work, we present a reconstruction of the standardized precipitation index (SPI) for the Iberian Range. Growth variations and climatic signals within the network are assessed developing a correlation matrix and the data combined to a single chronology integrating 336 samples from 169 trees of five different pine species distributed throughout the province of Teruel. The new chronology, calibrated against regional instrumental climatic data, shows a high and stable correlation with the July SPI integrating moisture conditions over 12 months forming the basis for a 318-year drought reconstruction. The climate signal contained in this reconstruction is highly significant (p < 0.05) and spatially robust over the interior areas of Spain located above 1000 meters above sea level (masl). According to our SPI reconstruction, seven substantially dry and five wet periods are identified since the late seventeenth century considering ≥±1.76 standard deviations. Besides these, 36 drought and 28 pluvial years were identified. Some of these years, such as 1725, 1741, 1803, and 1879, are also revealed in other drought reconstructions in Romania and Turkey, suggesting that coherent larger-scale synoptic patterns drove these extreme deviations. Since regional drought deviations are also retained in historical documents, the tree-ring-based reconstruction presented here will allow us to cross-validate drought frequency and magnitude in a highly vulnerable region.

Droughts in Amazonia: Spatiotemporal Variability, Teleconnections, and Seasonal Predictions

NASA Astrophysics Data System (ADS)

Lima, Carlos H. R.; AghaKouchak, Amir

2017-12-01

Most Amazonia drought studies have focused on rainfall deficits and their impact on river discharges, while the analysis of other important driver variables, such as temperature and soil moisture, has attracted less attention. Here we try to better understand the spatiotemporal dynamics of Amazonia droughts and associated climate teleconnections as characterized by the Palmer Drought Severity Index (PDSI), which integrates information from rainfall deficit, temperature anomalies, and soil moisture capacity. The results reveal that Amazonia droughts are most related to one dominant pattern across the entire region, followed by two seesaw kind of patterns: north-south and east-west. The main two modes are correlated with sea surface temperature (SST) anomalies in the tropical Pacific and Atlantic oceans. The teleconnections associated with global SST are then used to build a seasonal forecast model for PDSI over Amazonia based on predictors obtained from a sparse canonical correlation analysis approach. A unique feature of the presented drought prediction method is using only a few number of predictors to avoid excessive noise in the predictor space. Cross-validated results show correlations between observed and predicted spatial average PDSI up to 0.60 and 0.45 for lead times of 5 and 9 months, respectively. To the best of our knowledge, this is the first study in the region that, based on cross-validation results, leads to appreciable forecast skills for lead times beyond 4 months. This is a step forward in better understanding the dynamics of Amazonia droughts and improving risk assessment and management, through improved drought forecasting.

Are the traditional large-scale drought indices suitable for shallow water wetlands? An example in the Everglades.

PubMed

Zhao, Dehua; Wang, Penghe; Zuo, Jie; Zhang, Hui; An, Shuqing; Ramesh, Reddy K

2017-08-01

Numerous drought indices have been developed over the past several decades. However, few studies have focused on the suitability of indices for studies of ephemeral wetlands. The objective is to answer the following question: can the traditional large-scale drought indices characterize drought severity in shallow water wetlands such as the Everglades? The question was approached from two perspectives: the available water quantity and the response of wetland ecosystems to drought. The results showed the unsuitability of traditional large-scale drought indices for characterizing the actual available water quantity based on two findings. (1) Large spatial variations in precipitation (P), potential evapotranspiration (PE), water table depth (WTD) and the monthly water storage change (SC) were observed in the Everglades; notably, the spatial variation in SC, which reflects the monthly water balance, was 1.86 and 1.62 times larger than the temporal variation between seasons and between years, respectively. (2) The large-scale water balance measured based on the water storage variation had an average indicating efficiency (IE) of only 60.01% due to the redistribution of interior water. The spatial distribution of variations in the Normalized Different Vegetation Index (NDVI) in the 2011 dry season showed significantly positive, significantly negative and weak correlations with the minimum WTD in wet prairies, graminoid prairies and sawgrass wetlands, respectively. The significant and opposite correlations imply the unsuitability of the traditional large-scale drought indices in evaluating the effect of drought on shallow water wetlands. Copyright © 2017 Elsevier Ltd. All rights reserved.

An assessment of the ability of Bartlett-Lewis type of rainfall models to reproduce drought statistics

NASA Astrophysics Data System (ADS)

Pham, M. T.; Vanhaute, W. J.; Vandenberghe, S.; De Baets, B.; Verhoest, N. E. C.

2013-12-01

Of all natural disasters, the economic and environmental consequences of droughts are among the highest because of their longevity and widespread spatial extent. Because of their extreme behaviour, studying droughts generally requires long time series of historical climate data. Rainfall is a very important variable for calculating drought statistics, for quantifying historical droughts or for assessing the impact on other hydrological (e.g. water stage in rivers) or agricultural (e.g. irrigation requirements) variables. Unfortunately, time series of historical observations are often too short for such assessments. To circumvent this, one may rely on the synthetic rainfall time series from stochastic point process rainfall models, such as Bartlett-Lewis models. The present study investigates whether drought statistics are preserved when simulating rainfall with Bartlett-Lewis models. Therefore, a 105 yr 10 min rainfall time series obtained at Uccle, Belgium is used as a test case. First, drought events were identified on the basis of the Effective Drought Index (EDI), and each event was characterized by two variables, i.e. drought duration (D) and drought severity (S). As both parameters are interdependent, a multivariate distribution function, which makes use of a copula, was fitted. Based on the copula, four types of drought return periods are calculated for observed as well as simulated droughts and are used to evaluate the ability of the rainfall models to simulate drought events with the appropriate characteristics. Overall, all Bartlett-Lewis model types studied fail to preserve extreme drought statistics, which is attributed to the model structure and to the model stationarity caused by maintaining the same parameter set during the whole simulation period.

Estimating drought risk across Europe from reported drought impacts, drought indices, and vulnerability factors

NASA Astrophysics Data System (ADS)

Blauhut, Veit; Stahl, Kerstin; Stagge, James Howard; Tallaksen, Lena M.; De Stefano, Lucia; Vogt, Jürgen

2016-07-01

Drought is one of the most costly natural hazards in Europe. Due to its complexity, drought risk, meant as the combination of the natural hazard and societal vulnerability, is difficult to define and challenging to detect and predict, as the impacts of drought are very diverse, covering the breadth of socioeconomic and environmental systems. Pan-European maps of drought risk could inform the elaboration of guidelines and policies to address its documented severity and impact across borders. This work tests the capability of commonly applied drought indices and vulnerability factors to predict annual drought impact occurrence for different sectors and macro regions in Europe and combines information on past drought impacts, drought indices, and vulnerability factors into estimates of drought risk at the pan-European scale. This hybrid approach bridges the gap between traditional vulnerability assessment and probabilistic impact prediction in a statistical modelling framework. Multivariable logistic regression was applied to predict the likelihood of impact occurrence on an annual basis for particular impact categories and European macro regions. The results indicate sector- and macro-region-specific sensitivities of drought indices, with the Standardized Precipitation Evapotranspiration Index (SPEI) for a 12-month accumulation period as the overall best hazard predictor. Vulnerability factors have only limited ability to predict drought impacts as single predictors, with information about land use and water resources being the best vulnerability-based predictors. The application of the hybrid approach revealed strong regional and sector-specific differences in drought risk across Europe. The majority of the best predictor combinations rely on a combination of SPEI for shorter and longer accumulation periods, and a combination of information on land use and water resources. The added value of integrating regional vulnerability information with drought risk prediction could be proven. Thus, the study contributes to the overall understanding of drivers of drought impacts, appropriateness of drought indices selection for specific applications, and drought risk assessment.

Satellite-Based Drought Reporting on the Navajo Nation

NASA Technical Reports Server (NTRS)

McCullum, Amber; Schmidt, Cynthia; Ly, Vickie; Green, Rachel; McClellan, Carlee

2017-01-01

The Navajo Nation (NN) is the largest reservation in the US, and faces challenges related to water management during long-term and widespread drought episodes. The Navajo Nation is a federally recognized tribe, which has boundaries within Arizona, New Mexico, and Utah. The Navajo Nation has a land area of over 70,000 square kilometers. The Navajo Nation Department of Water Resources (NNDWR) reports on drought and climatic conditions through the use of regional Standardized Precipitation Index (SPI) values and a network of in-situ rainfall, streamflow, and climate data. However, these data sources lack the spatial detail and consistent measurements needed to provide a coherent understanding of the drought regime within the Nation's regional boundaries. This project, as part of NASA's Western Water Applications Office (WWAO), improves upon the recently developed Drought Severity Assessment Tool (DSAT) to ingest satellite-based precipitation data to generate SPI values for specific administrative boundaries within the reservation. The tool aims to: (1) generate SPI values and summary statistics for regions of interest on various timescales, (2) to visualize SPI values within a web-map application, and (3) produce maps and comparative statistical outputs in the format required for annual drought reporting. The co-development of the DSAT with NN partners is integral to increasing the sustained use of Earth Observations for water management applications. This tool will provide data to support the NN in allocation of drought contingency dollars to the regions most adversely impacted by declines in water availability.

Satellite-based Drought Reporting on the Navajo Nation

NASA Astrophysics Data System (ADS)

McCullum, A. J. K.; Schmidt, C.; Ly, V.; Green, R.; McClellan, C.

2017-12-01

The Navajo Nation (NN) is the largest reservation in the US, and faces challenges related to water management during long-term and widespread drought episodes. The Navajo Nation is a federally recognized tribe, which has boundaries within Arizona, New Mexico, and Utah. The Navajo Nation has a land area of over 70,000 square kilometers. The Navajo Nation Department of Water Resources (NNDWR) reports on drought and climatic conditions through the use of regional Standardized Precipitation Index (SPI) values and a network of in-situ rainfall, streamflow, and climate data. However, these data sources lack the spatial detail and consistent measurements needed to provide a coherent understanding of the drought regime within the Nation's regional boundaries. This project, as part of NASA's Western Water Applications Office (WWAO), improves upon the recently developed Drought Severity Assessment Tool (DSAT) to ingest satellite-based precipitation data to generate SPI values for specific administrative boundaries within the reservation. The tool aims to: (1) generate SPI values and summary statistics for regions of interest on various timescales, (2) to visualize SPI values within a web-map application, and (3) produce maps and comparative statistical outputs in the format required for annual drought reporting. The co-development of the DSAT with NN partners is integral to increasing the sustained use of Earth Observations for water management applications. This tool will provide data to support the NN in allocation of drought contingency dollars to the regions most adversely impacted by declines in water availability.

Diverse responses of different structured forest to drought in Southwest China through remotely sensed data

NASA Astrophysics Data System (ADS)

Xu, Peipei; Zhou, Tao; Zhao, Xiang; Luo, Hui; Gao, Shan; Li, Zheng; Cao, Leyao

2018-07-01

Global climate change leads to gradual increases in the frequency, intensity, and duration of extreme drought events. Human activities such as afforestation and deforestation have led to spatial variation in forest structure, causing forests to exhibit an age-spatial structure relationship. Thus, it is of great importance to accurately evaluate the effects of drought stress on forest ecosystems with different forest age structures. Because the spatial heterogeneity varies with drought stress intensity, forest age, there are still a lot of uncertainties in current studies. In this study, based on the field measurement, and the proxy index of stand age (based on forest canopy height from LiDAR and stock volume from inventory) at the regional scale, we analyzed the different drought responses of forest ecosystems with various forest ages across different scales in Yunnan province, southwest China from 2001 to 2014. At the local scale, significant differences in the effects of drought stress were found among forests with various ages, suggesting that older forests suffer more under drought stress than younger forests. At the regional scale, the investigation statistics of forest damage indicated a maximum damage ratio in the forest with tall trees (>32 m), whereas damage was minimal in the forest with short trees (<25 m). The stock volume of the forest exhibited the same pattern, that is, the forest damage ratio increased as the stock volume increased. These data demonstrate that the responses of forest drought could be affected by forest age. Under drought stress, older forests show greater vulnerability and risk of damage, which will require special attention for forest managers, as well as improved risk assessments, in the context of future climate change.

Spatio-temporal trends of drought by forest type in the conterminous United States, 1960-2013

Treesearch

Matthew P. Peters; Louis R. Iverson; Stephen N. Matthews

2014-01-01

Droughts are common in virtually all U.S. forests, but their frequency and intensity vary within forest ecosystems (Hanson and Weltzin 2000). Accounting for the long-term influence of droughts within a region is difficult due to variations in the spatial extent and intensities over a period. Therefore, we created a cumulative drought severity index (CDSI) (Fig. 1) for...

Role of large-scale atmospheric processes in variability of droughts in Ukraine

NASA Astrophysics Data System (ADS)

Khokhlov, Valeriy; Yermolenko, Nataliia

2015-04-01

We used the multiscalar drought index - standardized precipitation evapotranspiration index (SPEI) - to investigate the variability of droughts during the period of 1951-2010. The index allows considering the meteorological, agriculture and hydrological droughts. In this study, SPEI was calculated using the 0.5 degree grid data on the temperature and precipitation. The analysis was performed for the time series of four sites that are characteristic for the different parts of Ukraine - Chernihiv (Northern Ukraine), Odessa (Southern Ukraine), Uzhhorod (Western Ukraine), and Luhansk (Eastern Ukraine). The analysis revealed the periods with moistest and driest conditions. For the all sites, the moistest years were registered in the end of 1970s - start of 1980s. Moreover, both the number and intensity of droughts increase significantly since 1980, especially for the Southern Ukraine. During the 2006-2009, the most extreme and long drought was observed in the Odessa region. The analysis also showed that hydrological droughts begin with some delay from the meteorological ones, and have maximal duration. We used CUSUM method in order to detect specific years, when the significant change points occurred in the time series of droughts. This method also detected the start of 1980s as the years of transition from the moist to the dry conditions. The cross-wavelet transform was applied to reveal a connection between the droughts in Ukraine and teleconnection patterns in the North Atlantics. The analysis showed that the North Atlantic Oscillation (NAO) has a maximal effect on the droughts in Ukraine. The anti-phase relation is registered for the joint fluctuations with the periods 2-3 years and is most prominent in the Southern Ukraine. On the contrary, the NAO has a small impact on the Northern Ukraine. This fact can be explained by the orientation of main storm tracks for positive and negative phases of the NAO. The importance of long term planning of water management activities, varying from yearly reservoir rule curve determination to advice on crop selection given expected drought or flooding, increases as water becomes more scarce and event become more extreme. This work examines potential predictors for droughts in Ukriane to be used in optimization of long term planning.

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

PubMed

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

2008-08-08

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

Agricultural drought assessment using remotely sensed data in Central America

NASA Astrophysics Data System (ADS)

Nguyen, S. T.; Chen, C. F.; Chen, C. R.

2017-12-01

Central America is one of the world's regions most vulnerable to negative effects of agricultural drought due to impacts of climate change. Famers in the region have been confronting risks of crop damages and production losses due to intense droughts throughout the growing seasons. Drought information is thus deemed vital for policymakers to assess their crop management strategies in tackling issues of food insecurity in the region. This study aimed to delineate drought-prone areas associated with cropped areas from eight-day MODIS data in 2016 using the commonly used temperature dryness vegetation index (TVDI), calculated based on the land surface temperature (LST) and enhanced vegetation index (EVI) data. The advantages of MODIS data for agricultural drought monitoring at a national/regional scale are that it has the spatial resolution (500 m-1 km) and relatively high temporal resolution of eight days, but the data are often contaminated by clouds. Detecting and reconstructing the data under cloud-affected areas are generally a challenging task without any robust methods up to date. In this study, we reconstructed the eight-day MODIS EVI and LST data for agricultural drought assessment using machine-learning approaches. The reconstructed data were then used for drought assessment. The TVDI results verified with the soil moisture active passive (SMAP) data showed that the correlation coefficient values (r) obtained for the apante season (December-March) were between -0.4 to -0.8, while the values for the primera season (April-August) and postrera season (September-November) were in ranges of 0 to -0.6 and -0.2 to -0.7, respectively. The larger area of very dry soil moisture was generally observed during the dry season (December-April) and declined in the rainy season (May-November). The cropping areas affected by severe and moderate droughts observed for the primera season were respectively 11,846 km2 and 60,557 km2, while the values for the postera season were 14,174 km2 and 56,809 km2, and those for the postera season were 16,532 km2 and 40,018 km2, respectively. This study could provide quantitative information on distributions of drought at an eight-day interval, which is important to assist officials to mitigate economic costs for vulnerable populations in drought-prone areas.

Development of an operational African Drought Monitor prototype

NASA Astrophysics Data System (ADS)

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

2011-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

Investigation of hydrological drought using Cumulative Standardized Precipitation Index (SPI 30) in the eastern Mediterranean region (Damascus, Syria)

NASA Astrophysics Data System (ADS)

Zakhem, Boulos Abou; Kattaa, Bassam

2016-07-01

The Eastern Mediterranean region has been exposed to drought episodes, which have been occurring more frequently during the last decades. The objective of the present paper is to study the precipitation regime of the Damascus (Mazzeh) meteoric station by analysing drought characteristics using the Standardized Precipitation Index (SPI) and comparing this with the drought in Cyprus. The cumulative drought conceptis proposed to characterize long-term hydrologic drought, which affects the shallow groundwater productivity in terms of quantity and quality. Gamma probability distribution was fitted to the long-term annual precipitation in Damascus from 1918-1919 to 2007-2008 ( n = 90 years). Generally, a decreasing trend of 17% to the mean annual rainfall of Damascus and 13% to the mean annual rainfall of Cyprus was estimated between 1970 and 2000. The SPI identifies three major extended drought periods: (1) 9 years of severe drought (1954-1963) with an average 20% precipitation deficit per year compared to the mean. (2) 8 years of severe drought (1983-1991) with a 27% deficit per year on average. (3) 9 years of extreme drought (1993-2002) with a 31% deficit per year on average. The cumulative standardized precipitation index (SPI 30) demonstrates positive values for the first period and is indicative of having no effect on the global water balance. SPI 30 exhibits sensitive equilibrium with near zero values / a near zero value (±1.5) for the second period. For the third period, however, the SPI 30 decreases below -10 indicating an extreme hydrological drought that has negative consequences on the recent groundwater recharge. It is required to develop and implement a sustainable groundwater management strategy to reduce long-terms drought risks. Generally, the SPI 30 in Cyprus is parallel to that in Damascus with a 3-5 year delay. Thus, the central zone of the Eastern Mediterranean region is facing big challenges and has been suffering from three decades of moderate to severe hydrological drought (SPI 30=-5 to -10) causing a severe decrease in springs discharges of the region. Therefore, in order to reduce the climate change effects on water resources, it is necessary to adopt a sustainable proactive management plan during the frequent severe droughts.

Characterizing changes in drought risk for the United States from climate change

EPA Science Inventory

The effect of climate change on the frequency and intensity of droughts across the contiguous United States over the next century is assessed by applying Standardized Precipitation Indices and the Palmer Drought Severity Index to the full suite of 22 Intergovernmental Panel on Cl...

Vulnerability assessment in a participatory approach to design and implement community based adaptation to drought in the Peruvian Andes

NASA Astrophysics Data System (ADS)

Lasage, Ralph; Muis, Sanne; Sardella, Carolina; van Drunen, Michiel; Verburg, Peter; Aerts, Jeroen

2015-04-01

The livelihoods of people in the Andes are expected to be affected by climate change due to their dependence on glacier meltwater during the growing season. The observed decrease in glacier volume over the last few decades is likely to accelerate during the current century, which will affect water availability in the region. This paper presents the implementation of an approach for the participatory development of community-based adaptation measures to cope with the projected impacts of climate change, which was implemented jointly by the local community and by a team consisting of an NGO, Peruvian ministry of environment, research organisations and a private sector organisation. It bases participatory design on physical measurements, modelling and a vulnerability analysis. Vulnerability to drought is made operational for households in a catchment of the Ocoña river basin in Peru. On the basis of a household survey we explore how a vulnerability index (impacts divided by the households' perceived adaptive capacity) can be used to assess the distribution of vulnerability over households in a sub catchment. The socio-economic factors water entitlement, area of irrigated land, income and education are all significantly correlate with this vulnerability to drought. The index proved to be appropriate for communicating about vulnerability to climate change and its determining factors with different stakeholders. The water system research showed that the main source of spring water is local rainwater, and that water use efficiency in farming is low. The adaptation measures that were jointly selected by the communities and the project team aimed to increase water availability close to farmland, and increase water use efficiency, and these will help to reduce the communities vulnerability to drought.

An index for drought induced financial risk in the mining industry

NASA Astrophysics Data System (ADS)

Bonnafous, L.; Lall, U.; Siegel, J.

2017-02-01

Water scarcity has emerged as a potential risk for mining operations. High capital spending for desalination and water conflicts leading to asset stranding have recently occurred. Investors in mining companies are interested in the exposure to such risks across portfolios of mining assets (whether the practical at-site consequences are foregone production, higher OPEX and CAPEX and ensuing lost revenues, or asset-stranding). In this paper, an index of the potential financial exposure of a portfolio is developed and its application is illustrated. Since the likely loss at each mine is hard to estimate a priori, one needs a proxy for potential loss. The index considers drought duration, severity and frequency (defined by a return-level in years) at each mining asset, and provides a measure of financial exposure through weighing of production or Net Asset Value. Changes in human needs are not considered, but are relevant, and could be incorporated if global data on mine and other water use were available at the appropriate resolution. Potential for contemporaneous drought incidence across sites in a portfolio is considered specifically. Through an appropriate choice of drought thresholds, an analyst can customize a scenario to assess potential losses in production value or profits, or whether conflicts could emerge that would lead to stranded assets or capital expenditure to secure alternate water supplies. Global climate data sets that allow a customized development of such an index are identified, and selected mining company portfolios are scored as to the risk associated with one publicly available drought index.

Identification of the influencing factors on groundwater drought and depletion in north-western Bangladesh

NASA Astrophysics Data System (ADS)

Mustafa, Syed Md. Touhidul; Abdollahi, Khodayar; Verbeiren, Boud; Huysmans, Marijke

2017-08-01

Groundwater drought is a specific type of hydrological drought that concerns groundwater bodies. It may have a significant adverse effect on the socio-economic, agricultural, and environmental conditions. Investigating the effect of different climatic and anthropogenic factors on groundwater drought provides essential information for sustainable planning and management of (ground) water resources. The aim of this study is to identify the influencing factors on groundwater drought in north-western Bangladesh, to understand the forcing mechanisms. A multi-step methodology is proposed to achieve this objective. The standardised precipitation index (SPI) and reconnaissance drought index (RDI) have been used to quantify the aggregated deficit between precipitation and the evaporative demand of the atmosphere, i.e. meteorological drought. The influence of land-cover patterns on the groundwater drought has been identified by calculating spatially distributed groundwater recharge as a function of land cover. Groundwater drought is defined by a threshold method. The results show that the evapotranspiration and rainfall deficits are determining meteorological drought, which shows a direct relation with groundwater recharge deficits. Land-cover change has a small effect on groundwater recharge but does not seem to be the main cause of groundwater-level decline (depletion) in the study area. The groundwater depth and groundwater-level deficit (drought) is continuously increasing with little correlation to meteorological drought or recharge anomalies. Overexploitation of groundwater for irrigation seems to be the main cause of groundwater-level decline in the study area. Efficient irrigation management is essential to reduce the growing pressure on groundwater resources and ensure sustainable water management.

An assessment of climate and fire danger rating in the Northern Rockies during the 1910 fire season

Treesearch

Charles W. McHugh; Mark A. Finney; Larry S. Bradshaw

2010-01-01

The 1910 fires of western Montana and northern Idaho have received much publicity in the popular media but little scientific attention regarding the factors that contribute to fire behavior and fire danger. Here we present information surrounding the weather, and reconstructed measures of Palmer Drought Severity Index (PDSI), Keetch-Byram Drought Index (KBDI), Energy...

Predicting the Vegetation Condition of the 2015/16 Drought across the Great Horn of Africa (GHA): Model Evaluation and Preliminary Result

NASA Astrophysics Data System (ADS)

Tadesse, T.; Bayissa, Y. A.; Demisse, G. B.; Wardlow, B.

2017-12-01

The National Drought Mitigation Center (NDMC) funded by NASA has developed a new tool for predicting the general vegetation condition called: the "Vegetation outlook for the Greater Africa (VegOut-GHA)." In this study, the 2015/16 drought across the GHA that has been considered one of the worst in decades across the region was assessed and evaluated using the VegOut-GHA models and products. The VegOut-GHA maps (hindsight prediction maps) for the growing season (June - September) were generated to predict a standardized seasonal greenness (SSG) that is based on seasonally integrated normalized difference vegetation index (a measure that represents a general indicator of relative vegetation health within a growing season). The vegetation condition outlooks were made for 10-day, 1-month, 2-month, and 3-month in hindsight and compared to the observed values of the SSG. The VegOut-GHA model was evaluated and compared to crop yield and other satellite-derived data (e.g., standardized seasonal precipitation based on "Enhancing National Climate Services (ENACTS)" datasets for GHA). Thus, the VegOut-GHA model and its evaluation results will be discussed based on the 2015/2016 drought season in the region. This preliminary results suggest an opportunity to improve management of drought risk in agriculture and food security.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

A new framework for evaluating the impacts of drought on net primary productivity of grassland.

PubMed

Lei, Tianjie; Wu, Jianjun; Li, Xiaohan; Geng, Guangpo; Shao, Changliang; Zhou, Hongkui; Wang, Qianfeng; Liu, Leizhen

2015-12-01

This paper presented a valuable framework for evaluating the impacts of droughts (single factor) on grassland ecosystems. This framework was defined as the quantitative magnitude of drought impact that unacceptable short-term and long-term effects on ecosystems may experience relative to the reference standard. Long-term effects on ecosystems may occur relative to the reference standard. Net primary productivity (NPP) was selected as the response indicator of drought to assess the quantitative impact of drought on Inner Mongolia grassland based on the Standardized Precipitation Index (SPI) and BIOME-BGC model. The framework consists of six main steps: 1) clearly defining drought scenarios, such as moderate, severe and extreme drought; 2) selecting an appropriate indicator of drought impact; 3) selecting an appropriate ecosystem model and verifying its capabilities, calibrating the bias and assessing the uncertainty; 4) assigning a level of unacceptable impact of drought on the indicator; 5) determining the response of the indicator to drought and normal weather state under global-change; and 6) investigating the unacceptable impact of drought at different spatial scales. We found NPP losses assessed using the new framework were more sensitive to drought and had higher precision than the long-term average method. Moreover, the total and average losses of NPP are different in different grassland types during the drought years from 1961-2009. NPP loss was significantly increased along a gradient of increasing drought levels. Meanwhile, NPP loss variation under the same drought level was different in different grassland types. The operational framework was particularly suited for integrative assessing the effects of different drought events and long-term droughts at multiple spatial scales, which provided essential insights for sciences and societies that must develop coping strategies for ecosystems for such events. Copyright © 2015 Elsevier B.V. All rights reserved.

Drought prediction till 2100 under RCP 8.5 climate change scenarios for Korea

NASA Astrophysics Data System (ADS)

Park, Chang-Kyun; Byun, Hi-Ryong; Deo, Ravinesh; Lee, Bo-Ra

2015-07-01

An important step in mitigating the negative impacts of drought requires effective methodologies for predicting the future events. This study utilises the daily Effective Drought Index (EDI) to precisely and quantitatively predict future drought occurrences in Korea over the period 2014-2100. The EDI is computed from precipitation data generated by the regional climate model (HadGEM3-RA) under the Representative Concentration Pathway (RCP 8.5) scenario. Using this data for 678 grid points (12.5 km interval) groups of cluster regions with similar climates, the G1 (Northwest), G2 (Middle), G3 (Northeast) and G4 (Southern) regions, are constructed. Drought forecasting period is categorised into the early phase (EP, 2014-2040), middle phase (MP, 2041-2070) and latter phase (LP, 2071-2100). Future drought events are quantified and ranked according to the duration and intensity. Moreover, the occurrences of drought (when, where, how severe) within the clustered regions are represented as a spatial map over Korea. Based on the grid-point averages, the most severe future drought throughout the 87-year period are expected to occur in Namwon around 2039-2041 with peak intensity (minimum EDI) -3.54 and projected duration of 580 days. The most severe drought by cluster analysis is expected to occur in the G3 region with a mean intensity of -2.85 in 2027. Within the spatial area of investigation, 6.6 years of drought periodicity and a slight decrease in the peak intensity is noted. Finally a spatial-temporal drought map is constructed for all clusters and time-periods under consideration.

Drought Prediction till 2100 Under RCP 8.5 Climate Change Scenarios for Korea

NASA Astrophysics Data System (ADS)

Byun, H. R.; Park, C. K.; Deo, R. C.

2014-12-01

An important step in mitigating the negative impacts of drought requires effective methodologies for predicting the future events. This study utilizes the daily Effective Drought Index (EDI) to precisely and quantitatively predict future drought occurrences in Korea over the period 2014-2100. The EDI is computed from precipitation data generated by the regional climate model (HadGEM3-RA) under the Representative Concentration Pathway (RCP 8.5) scenario. Using this data for 678 grid points (12.5 km interval) groups of cluster regions with similar climates, the G1 (Northwest), G2 (Middle), G3 (Northeast) and G4 (Southern) regions, are constructed. Drought forecasting period is categorised into the early phase (EP, 2014-2040), middle phase (MP, 2041-2070) and latter phase (LP, 2071-2100). Future drought events are quantified and ranked according to the duration and intensity. Moreover, the occurrences of drought (when, where, how severe) within the clustered regions are represented as a spatial map over Korea. Based on the grid-point averages, the most severe future drought throughout the 87-year period are expected to occur in Namwon around 2039-2041 with peak intensity (minimum EDI) -3.54 and projected duration of 580 days. The most severe drought by cluster analysis is expected to occur in the G3 region with a mean intensity of -2.85 in 2027. Within the spatial area of investigation, 6 years of drought periodicity and a slight decrease in the peak intensity is noted. Finally a spatial-temporal drought map is constructed for all clusters and time-periods under consideration.

Assessment of drought during corn growing season in Northeast China

NASA Astrophysics Data System (ADS)

Zhang, Qi; Hu, Zhenghua

2018-04-01

Northeast China has experienced extensive climate change during the past decades. Corn is the primary production crop in China and is sensitive to meteorological disasters, especially drought. Drought has thus greatly endangered crop production and the country's food security. The majority of previous studies has not highlighted farming adaptation activities undertaken within the changed climate, which should not be neglected. In this study, we assessed drought hazard in the corn vegetation growing period, the reproductive growing period, and the whole growing period based on data for yearly corn phenology, daily precipitation, and temperature gathered at 26 agro-meteorological stations across Northeast China from 1981 to 2009. The M-K trend test was used to detect trends in sowing date and drought. The standardized precipitation evapotranspiration index (SPEI) was used to describe drought. Drought frequency and intensity were used to assess the drought hazard in the region. We found that the sowing date was delayed in the southern part of the study area, coupled with a trend towards a shorter and more humid vegetation growing period. In the northern part of the study area, an earlier sowing date increased the length of the vegetation growing period and the reproductive growing period, while drying trends occurred within the two corn growing periods. We assessed the drought hazard during each growing period: the reproductive growing period faced a more severe drought hazard and was also the period where corn was most sensitive to water stress. Drought hazard during the total growing period was closely related to corn yield.

Drought assessment using a TRMM-derived standardized precipitation index for the upper São Francisco River basin, Brazil.

PubMed

Santos, Celso Augusto Guimarães; Brasil Neto, Reginaldo Moura; Passos, Jacqueline Sobral de Araújo; da Silva, Richarde Marques

2017-06-01

In this work, the use of Tropical Rainfall Measuring Mission (TRMM) rainfall data and the Standardized Precipitation Index (SPI) for monitoring spatial and temporal drought variabilities in the Upper São Francisco River basin is investigated. Thus, the spatiotemporal behavior of droughts and cluster regions with similar behaviors is identified. As a result, the joint analysis of clusters, dendrograms, and the spatial distribution of SPI values proved to be a powerful tool in identifying homogeneous regions. The results showed that the northeast region of the basin has the lowest rainfall indices and the southwest region has the highest rainfall depths, and that the region has well-defined dry and rainy seasons from June to August and November to January, respectively. An analysis of the drought and rain conditions showed that the studied region was homogeneous and well-distributed; however, the quantity of extreme and severe drought events in short-, medium- and long-term analysis was higher than that expected in regions with high rainfall depths, particularly in the south/southwest and southeast areas. Thus, an alternative classification is proposed to characterize the drought, which spatially categorizes the drought type (short-, medium-, and long-term) according to the analyzed drought event type (extreme, severe, moderate, and mild).

Spatiotemporal analysis of hydro-meteorological drought in the Johor River Basin, Malaysia

NASA Astrophysics Data System (ADS)

Tan, Mou Leong; Chua, Vivien P.; Li, Cheng; Brindha, K.

2018-02-01

Assessment of historical hydro-meteorological drought is important to develop a robust drought monitoring and prediction system. This study aims to assess the historical hydro-meteorological drought of the Johor River Basin (JRB) from 1975 to 2010, an important basin for the population of southern Peninsular Malaysia and Singapore. The Standardized Precipitation Index (SPI) and Standardized Streamflow Index (SSI) were selected to represent the meteorological and hydrological droughts, respectively. Four absolute homogeneity tests were used to assess the rainfall data from 20 stations, and two stations were flagged by these tests. Results indicate the SPI duration to be comparatively low (3 months), and drier conditions occur over the upper JRB. The annual SSI had a strong decreasing trend at 95% significance level, showing that human activities such as reservoir construction and agriculture (oil palm) have a major influence on streamflow in the middle and lower basin. In addition, moderate response rate of SSI to SPI was found, indicating that hydrological drought could also have occurred in normal climate condition. Generally, the El Niño-Southern Oscillation and Madden Julian Oscillation have greater impacts on drought events in the basin. Findings of this study could be beneficial for future drought projection and water resources management.

Spatial and temporal analysis of drought variability at several time scales in Syria during 1961-2012

NASA Astrophysics Data System (ADS)

Mathbout, Shifa; Lopez-Bustins, Joan A.; Martin-Vide, Javier; Bech, Joan; Rodrigo, Fernando S.

2018-02-01

This paper analyses the observed spatiotemporal characteristics of drought phenomenon in Syria using the Standardised Precipitation Index (SPI) and the Standardised Precipitation Evapotranspiration Index (SPEI). Temporal variability of drought is calculated for various time scales (3, 6, 9, 12, and 24 months) for 20 weather stations over the 1961-2012 period. The spatial patterns of drought were identified by applying a Principal Component Analysis (PCA) to the SPI and SPEI values at different time scales. The results revealed three heterogeneous and spatially well-defined regions with different temporal evolution of droughts: 1) Northeastern (inland desert); 2) Southern (mountainous landscape); 3) Northwestern (Mediterranean coast). The evolutionary characteristics of drought during 1961-2012 were analysed including spatial and temporal variability of SPI and SPEI, the frequency distribution, and the drought duration. The results of the non-parametric Mann-Kendall test applied to the SPI and SPEI series indicate prevailing significant negative trends (drought) at all stations. Both drought indices have been correlated both on spatial and temporal scales and they are highly comparable, especially, over a 12 and 24 month accumulation period. We concluded that the temporal and spatial characteristics of the SPI and SPEI can be used for developing a drought intensity - areal extent - and frequency curve that assesses the variability of regional droughts in Syria. The analysis of both indices suggests that all three regions had a severe drought in the 1990s, which had never been observed before in the country. Furthermore, the 2007-2010 drought was the driest period in the instrumental record, happening just before the onset of the recent conflict in Syria.

Prospects for seasonal forecasting of summer drought and low river flow anomalies in England and Wales

NASA Astrophysics Data System (ADS)

Wedgbrow, C. S.; Wilby, R. L.; Fox, H. R.; O'Hare, G.

2002-02-01

Future climate change scenarios suggest enhanced temporal and spatial gradients in water resources across the UK. Provision of seasonal forecast statistics for surface climate variables could alleviate some negative effects of climate change on water resource infrastructure. This paper presents a preliminary investigation of spatial and temporal relationships between large-scale North Atlantic climatic indices, drought severity and river flow anomalies in England and Wales. Potentially useful predictive relationships are explored between winter indices of the Polar-Eurasian (POL) teleconnection pattern, the North Atlantic oscillation (NAO), North Atlantic sea surface temperature anomalies (SSTAs), and the summer Palmer drought severity index (PDSI) and reconstructed river flows in England and Wales. Correlation analyses, coherence testing and an index of forecast potential, demonstrate that preceding winter values of the POL index, SSTA (and to a lesser extent the NAO), provide indications of summer and early autumn drought severity and river flow anomalies in parts of northwest, southwest and southeast England. Correlation analyses demonstrate that positive winter anomalies of T1, POL index and NAO index are associated with negative PDSI (i.e. drought) across eastern parts of the British Isles in summer (r < 0.51). Coherence tests show that a positive winter SSTA (1871-1995) and POL index (1950-95) have preceded below-average summer river flows in the northwest and southwest of England and Wales in 70 to 100% of summers. The same rivers have also experienced below-average flows during autumn following negative winter phases of the NAO index in 64 to 93% of summers (1865-1995). Possible explanations for the predictor-predictand relationships are considered, including the memory of groundwater, and ocean-atmosphere coupling, and regional manifestations of synoptic rainfall processes. However, further research is necessary to increase the number of years and predictor variables from which it is possible to derive rules that may be useful for forecasting.

Application of the extreme learning machine algorithm for the prediction of monthly Effective Drought Index in eastern Australia

NASA Astrophysics Data System (ADS)

Deo, Ravinesh C.; Şahin, Mehmet

2015-02-01

The prediction of future drought is an effective mitigation tool for assessing adverse consequences of drought events on vital water resources, agriculture, ecosystems and hydrology. Data-driven model predictions using machine learning algorithms are promising tenets for these purposes as they require less developmental time, minimal inputs and are relatively less complex than the dynamic or physical model. This paper authenticates a computationally simple, fast and efficient non-linear algorithm known as extreme learning machine (ELM) for the prediction of Effective Drought Index (EDI) in eastern Australia using input data trained from 1957-2008 and the monthly EDI predicted over the period 2009-2011. The predictive variables for the ELM model were the rainfall and mean, minimum and maximum air temperatures, supplemented by the large-scale climate mode indices of interest as regression covariates, namely the Southern Oscillation Index, Pacific Decadal Oscillation, Southern Annular Mode and the Indian Ocean Dipole moment. To demonstrate the effectiveness of the proposed data-driven model a performance comparison in terms of the prediction capabilities and learning speeds was conducted between the proposed ELM algorithm and the conventional artificial neural network (ANN) algorithm trained with Levenberg-Marquardt back propagation. The prediction metrics certified an excellent performance of the ELM over the ANN model for the overall test sites, thus yielding Mean Absolute Errors, Root-Mean Square Errors, Coefficients of Determination and Willmott's Indices of Agreement of 0.277, 0.008, 0.892 and 0.93 (for ELM) and 0.602, 0.172, 0.578 and 0.92 (for ANN) models. Moreover, the ELM model was executed with learning speed 32 times faster and training speed 6.1 times faster than the ANN model. An improvement in the prediction capability of the drought duration and severity by the ELM model was achieved. Based on these results we aver that out of the two machine learning algorithms tested, the ELM was the more expeditious tool for prediction of drought and its related properties.

Regional drought shifts (1710-2010) in East Central Asia and linkages with atmospheric circulation recorded in tree-ring δ18O

NASA Astrophysics Data System (ADS)

Xu, Guobao; Liu, Xiaohong; Trouet, Valerie; Treydte, Kerstin; Wu, Guoju; Chen, Tuo; Sun, Weizhen; An, Wenling; Wang, Wenzhi; Zeng, Xiaomin; Qin, Dahe

2018-04-01

Drought occurrence and duration in central Asia are of important socioeconomic, ecological, and geophysical significance and have received increasing research attention in recent years. Understanding long-term drought trends and their driving forces require reliable records of past drought variability with broad spatial representativeness. Here, we compiled four tree-ring δ18O records from eastern central Asia (ECA) and composited them into a drought-sensitive proxy to explore regional ECA moisture variations over the past 301 years (1710-2010 CE). A robust regional standardized precipitation-evapotranspiration index (SPEI) reconstruction was established based on the tree-ring cellulose δ18O fractionation mechanism and statistically significant proxy-climate relationships. We identified prominent droughts in 1710-1770, 1810-1830, and the beginning of the twenty-first century, and a regime shift to a persistently wet period from the 1880s to 2000. Our reconstruction reveals the impact of drought and pluvial patterns on the decline of Zhungar Empire, and on historical agricultural and socio-economical activities, including increased migration into ECA during the 1770-1800 pluvial. Our findings also suggest that wet conditions in the twentieth century in ECA were related to a strengthening of the westerly circulation and thus shed light on large-scale atmospheric circulation dynamics in central Asia.

Evaluation of Drought Occurrence and Climate Change in the Pearl River Basin in South China

NASA Astrophysics Data System (ADS)

DU, Y.; Chen, J.; Wang, K.; Shi, H.

2015-12-01

This study uses the Variable Infiltration Capacity (VIC) Model to simulate the hydrological processes over the Pearl River basin in South China. The observed streamflow data in the Pearl River Basin for the period 1951-2000 are used to evaluate the model simulation results. Further, in this study, the 55 datasets of climate projection from 18 General Circulation Models (GCMs) for the IPCC AR4 (SRES A2/A1B/B1) and AR5 (RCP 2.6/4.5/6.0/8.5) are used to drive the VIC model at 0.5°× 0.5°spatial resolution and daily temporal resolution. Then, the monthly Standard Precipitation Index (SPI) and standardized runoff index (SRI) are generated to detect the drought occurrence. This study validates the GCMs projection through comparing the observed precipitation for the period of 2000-2013. Then, spatial variation of the frequency change of moderate drought, severe drought and extreme drought are analyzed for the 21st century. The study reveals that the frequencies of severe drought and extreme drought occurrences over the Pearl River Basin increase along with time. Specifically, for the scenario of AR5 RCP 8.5, the east and west parts of the Pearl River Basin most likely suffer from severe drought and extreme drought with an increased frequency throughout the 21st century.

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

USGS Publications Warehouse

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

2017-01-01

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

Historical droughts in Mediterranean regions during the last 500 years: a data/model approach

NASA Astrophysics Data System (ADS)

Brewer, S.; Alleaume, S.; Guiot, J.; Nicault, A.

2007-06-01

We present here a new method for comparing the output of General Circulation Models (GCMs) with proxy-based reconstructions, using time series of reconstructed and simulated climate parameters. The method uses k-means clustering to allow comparison between different periods that have similar spatial patterns, and a fuzzy logic-based distance measure in order to take reconstruction errors into account. The method has been used to test two coupled ocean-atmosphere GCMs over the Mediterranean region for the last 500 years, using an index of drought stress, the Palmer Drought Severity Index. The results showed that, whilst no model exactly simulated the reconstructed changes, all simulations were an improvement over using the mean climate, and a good match was found after 1650 with a model run that took into account changes in volcanic forcing, solar irradiance, and greenhouse gases. A more detailed investigation of the output of this model showed the existence of a set of atmospheric circulation patterns linked to the patterns of drought stress: 1) a blocking pattern over northern Europe linked to dry conditions in the south prior to the Little Ice Age (LIA) and during the 20th century; 2) a NAO-positive like pattern with increased westerlies during the LIA; 3) a NAO-negative like period shown in the model prior to the LIA, but that occurs most frequently in the data during the LIA. The results of the comparison show the improvement in simulated climate as various forcings are included and help to understand the atmospheric changes that are linked to the observed reconstructed climate changes.

Drought propagation and its relation with catchment biophysical characteristics

NASA Astrophysics Data System (ADS)

Alvarez-Garreton, C. D.; Lara, A.; Garreaud, R. D.

2016-12-01

Droughts propagate in the hydrological cycle from meteorological to soil moisture to hydrological droughts. To understand the drivers of this process is of paramount importance since the economic and societal impacts in water resources are directly related with hydrological droughts (and not with meteorological droughts, which have been most studied). This research analyses drought characteristics over a large region and identify its main exogenous (climate forcing) and endogenous (biophysical characteristics such as land cover type and topography) explanatory factors. The study region is Chile, which covers seven major climatic subtypes according to Köppen system, it has unique geographic characteristics, very sharp topography and a wide range of landscapes and vegetation conditions. Meteorological and hydrological droughts (deficit in precipitation and streamflow, respectively) are characterized by their durations and standardized deficit volumes using a variable threshold method, over 300 representative catchments (located between 27°S and 50°S). To quantify the propagation from meteorological to hydrological drought, we propose a novel drought attenuation index (DAI), calculated as the ratio between the meteorological drought severity slope and the hydrological drought severity slope. DAI varies from zero (catchment that attenuates completely a meteorological drought) to one (the meteorological drought is fully propagated through the hydrological cycle). This novel index provides key (and comparable) information about drought propagation over a wide range of different catchments, which has been highlighted as a major research gap. Similar drought indicators across the wide range of catchments are then linked with catchment biophysical characteristics. A thorough compilation of land cover information (including the percentage of native forests, grass land, urban and industrial areas, glaciers, water bodies and no vegetated areas), catchment physical properties, and climatic conditions is done for all the catchments. Data mining techniques are applied to identify the main exogenous and endogenous factors determining drought characteristics and propagation.

Introducing an operational method to forecast long-term regional drought based on the application of artificial intelligence capabilities

NASA Astrophysics Data System (ADS)

Kousari, Mohammad Reza; Hosseini, Mitra Esmaeilzadeh; Ahani, Hossein; Hakimelahi, Hemila

2017-01-01

An effective forecast of the drought definitely gives lots of advantages in regard to the management of water resources being used in agriculture, industry, and households consumption. To introduce such a model applying simple data inputs, in this study a regional drought forecast method on the basis of artificial intelligence capabilities (artificial neural networks) and Standardized Precipitation Index (SPI in 3, 6, 9, 12, 18, and 24 monthly series) has been presented in Fars Province of Iran. The precipitation data of 41 rain gauge stations were applied for computing SPI values. Besides, weather signals including Multivariate ENSO Index (MEI), North Atlantic Oscillation (NAO), Southern Oscillation Index (SOI), NINO1+2, anomaly NINO1+2, NINO3, anomaly NINO3, NINO4, anomaly NINO4, NINO3.4, and anomaly NINO3.4 were also used as the predictor variables for SPI time series forecast the next 12 months. Frequent testing and validating steps were considered to obtain the best artificial neural networks (ANNs) models. The forecasted values were mapped in verification sector then they were compared with the observed maps at the same dates. Results showed considerable spatial and temporal relationships even among the maps of different SPI time series. Also, the first 6 months forecasted maps showed an average of 73 % agreements with the observed ones. The most important finding and the strong point of this study was the fact that although drought forecast in each station and time series was completely independent, the relationships between spatial and temporal predictions remained. This strong point mainly referred to frequent testing and validating steps in order to explore the best drought forecast models from plenty of produced ANNs models. Finally, wherever the precipitation data are available, the practical application of the presented method is possible.

Drought causes reduced growth of trembling aspen in western Canada.

PubMed

Chen, Lei; Huang, Jian-Guo; Alam, Syed Ashraful; Zhai, Lihong; Dawson, Andria; Stadt, Kenneth J; Comeau, Philip G

2017-07-01

Adequate and advance knowledge of the response of forest ecosystems to temperature-induced drought is critical for a comprehensive understanding of the impacts of global climate change on forest ecosystem structure and function. Recent massive decline in aspen-dominated forests and an increased aspen mortality in boreal forests have been associated with global warming, but it is still uncertain whether the decline and mortality are driven by drought. We used a series of ring-width chronologies from 40 trembling aspen (Populus tremuloides Michx.) sites along a latitudinal gradient (from 52° to 58°N) in western Canada, in an attempt to clarify the impacts of drought on aspen growth by using Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI). Results indicated that prolonged and large-scale droughts had a strong negative impact on trembling aspen growth. Furthermore, the spatiotemporal variability of drought indices is useful for explaining the spatial heterogeneity in the radial growth of trembling aspen. Due to ongoing global warming and rising temperatures, it is likely that severer droughts with a higher frequency will occur in western Canada. As trembling aspen is sensitive to drought, we suggest that drought indices could be applied to monitor the potential effects of increased drought stress on aspen trees growth, achieve classification of eco-regions and develop effective mitigation strategies to maintain western Canadian boreal forests. © 2017 John Wiley & Sons Ltd.

Physiological mechanisms contributing to the QTL-combination effects on improved performance of IR64 rice NILs under drought

PubMed Central

Henry, Amelia; Swamy, B. P. Mallikarjuna; Dixit, Shalabh; Torres, Rolando D.; Batoto, Tristram C.; Manalili, Mervin; Anantha, M. S.; Mandal, N. P.; Kumar, Arvind

2015-01-01

Characterizing the physiological mechanisms behind major-effect drought-yield quantitative trait loci (QTLs) can provide an understanding of the function of the QTLs—as well as plant responses to drought in general. In this study, we characterized rice (Oryza sativa L.) genotypes with QTLs derived from drought-tolerant traditional variety AdaySel that were introgressed into drought-susceptible high-yielding variety IR64, one of the most popular megavarieties in South Asian rainfed lowland systems. Of the different combinations of the four QTLs evaluated, genotypes with two QTLs (qDTY 2.2 + qDTY 4.1) showed the greatest degree of improvement under drought compared with IR64 in terms of yield, canopy temperature, and normalized difference vegetation index (NDVI). Furthermore, qDTY 2.2 and qDTY 4.1 showed a potential for complementarity in that they were each most effective under different severities of drought stress. Multiple drought-response mechanisms were observed to be conferred in the genotypes with the two-QTL combination: higher root hydraulic conductivity and in some cases greater root growth at depth. As evidenced by multiple leaf water status and plant growth indicators, these traits affected transpiration but not transpiration efficiency or harvest index. The results from this study highlight the complex interactions among major-effect drought-yield QTLs and the drought-response traits they confer, and the need to evaluate the optimal combinations of QTLs that complement each other when present in a common genetic background. PMID:25680791

Severe summer heatwave and drought strongly reduced carbon uptake in Southern China

DOE PAGES

Yuan, Wenping; Cai, Wenwen; Chen, Yang; ...

2016-01-07

Increasing heatwave and drought events can potentially alter the carbon cycle. Few studies have investigated the impacts of hundred-year return heatwaves and droughts, as those events are rare. In the summer of 2013, southern China experienced its strongest drought and heatwave on record for the past 113 years. We show that the record-breaking heatwave and drought lasted two months (from July to August), significantly reduced the satellite-based vegetation index and gross primary production, substantially altered the regional carbon cycle, and produced the largest negative crop yield anomaly since 1960. The event resulted in a net reduction of 101.54 Tg Cmore » in carbon sequestration in the region during these two months, which was 39–53% of the annual net carbon sink of China’s terrestrial ecosystems (190–260 Tg C yr -1). Moreover, model experiments showed that heatwaves and droughts consistently decreased ecosystem vegetation primary production but had opposite impacts on ecosystem respiration (TER), with increased TER by 6.78 ± 2.15% and decreased TER by 15.34 ± 3.57% assuming only changed temperature and precipitation, respectively. As a result, in light of increasing frequency and severity of future heatwaves and droughts, our study highlights the importance of accounting for the impacts of heatwaves and droughts in assessing the carbon sequestration in terrestrial ecosystems.« less

Severe summer heatwave and drought strongly reduced carbon uptake in Southern China

PubMed Central

Yuan, Wenping; Cai, Wenwen; Chen, Yang; Liu, Shuguang; Dong, Wenjie; Zhang, Haicheng; Yu, Guirui; Chen, Zhuoqi; He, Honglin; Guo, Weidong; Liu, Dan; Liu, Shaoming; Xiang, Wenhua; Xie, Zhenghui; Zhao, Zhonghui; Zhou, Guomo

2016-01-01

Increasing heatwave and drought events can potentially alter the carbon cycle. Few studies have investigated the impacts of hundred-year return heatwaves and droughts, as those events are rare. In the summer of 2013, southern China experienced its strongest drought and heatwave on record for the past 113 years. We show that the record-breaking heatwave and drought lasted two months (from July to August), significantly reduced the satellite-based vegetation index and gross primary production, substantially altered the regional carbon cycle, and produced the largest negative crop yield anomaly since 1960. The event resulted in a net reduction of 101.54 Tg C in carbon sequestration in the region during these two months, which was 39–53% of the annual net carbon sink of China’s terrestrial ecosystems (190–260 Tg C yr−1). Moreover, model experiments showed that heatwaves and droughts consistently decreased ecosystem vegetation primary production but had opposite impacts on ecosystem respiration (TER), with increased TER by 6.78 ± 2.15% and decreased TER by 15.34 ± 3.57% assuming only changed temperature and precipitation, respectively. In light of increasing frequency and severity of future heatwaves and droughts, our study highlights the importance of accounting for the impacts of heatwaves and droughts in assessing the carbon sequestration in terrestrial ecosystems. PMID:26739761

Severe summer heatwave and drought strongly reduced carbon uptake in Southern China

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

Yuan, Wenping; Cai, Wenwen; Chen, Yang

Increasing heatwave and drought events can potentially alter the carbon cycle. Few studies have investigated the impacts of hundred-year return heatwaves and droughts, as those events are rare. In the summer of 2013, southern China experienced its strongest drought and heatwave on record for the past 113 years. We show that the record-breaking heatwave and drought lasted two months (from July to August), significantly reduced the satellite-based vegetation index and gross primary production, substantially altered the regional carbon cycle, and produced the largest negative crop yield anomaly since 1960. The event resulted in a net reduction of 101.54 Tg Cmore » in carbon sequestration in the region during these two months, which was 39–53% of the annual net carbon sink of China’s terrestrial ecosystems (190–260 Tg C yr -1). Moreover, model experiments showed that heatwaves and droughts consistently decreased ecosystem vegetation primary production but had opposite impacts on ecosystem respiration (TER), with increased TER by 6.78 ± 2.15% and decreased TER by 15.34 ± 3.57% assuming only changed temperature and precipitation, respectively. As a result, in light of increasing frequency and severity of future heatwaves and droughts, our study highlights the importance of accounting for the impacts of heatwaves and droughts in assessing the carbon sequestration in terrestrial ecosystems.« less

Aerosol forcing of extreme summer drought over North China

NASA Astrophysics Data System (ADS)

Zhang, L.

2017-12-01

The frequency of extreme summer drought has been increasing in North China during the past sixty years, which has caused serious water shortages. It remains unclear whether anthropogenic forcing has contributed to the increasing extreme droughts. Using the National Centers for Environmental Prediction and the National Center for Atmospheric Research (NCEP/NCAR) re-analysis data and Coupled Model Intercomparison Project Phase 5 (CMIP5) model simulations with various combinations of historical forcings, the authors investigated the driving mechanism behind the observed changes. Metrological drought is usually measured by precipitation anomalies, which show lower fidelity in current climate models compared to largescale circulation patterns. Based on NCEP/NCAR re-analysis, a linear relationship is firstly established between the weakest regional average 850 hPa southerly winds and extreme summer drought. This meridional winds index (MWI) is then used as a proxy for attribution of extreme North China drought using CMIP5 outputs. Examination of the CMIP5 simulations reveals that the probability of the extreme summer droughts with the first percentile of MWI for 1850-2004 under anthropogenic forcing has increased by 100%, on average, relative to a pre-industrial control run. The more frequent occurrence of extremely weak MWIs or drought over North China is ascribed from weakened climate and East Asian summer monsoon (EASM) circulation due to the direct cooling effect from increased aerosol.

Modelling crop yield in Iberia under drought conditions

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

A Physically-Based Drought Product Using Thermal Remote Sensing of Evapotranspiration

USDA-ARS?s Scientific Manuscript database

Thermal infrared (TIR) remote sensing of land-surface temperature (LST) provides valuable information about the sub-surface moisture status. While empirical indices measuring anomalies in LST and vegetation amount (e.g., as quantified by the Normalized Difference Vegetation Index; NDVI) have demonst...

Assessment of climate change impacts on meteorological and hydrological droughts in the Jucar River Basin

NASA Astrophysics Data System (ADS)

Marcos-Garcia, Patricia; Pulido-Velazquez, Manuel; Lopez-Nicolas, Antonio

2016-04-01

Extreme natural phenomena, and more specifically droughts, constitute a serious environmental, economic and social issue in Southern Mediterranean countries, common in the Mediterranean Spanish basins due to the high temporal and spatial rainfall variability. Drought events are characterized by their complexity, being often difficult to identify and quantify both in time and space, and an universally accepted definition does not even exist. This fact, along with future uncertainty about the duration and intensity of the phenomena on account of climate change, makes necessary increasing the knowledge about the impacts of climate change on droughts in order to design management plans and mitigation strategies. The present abstract aims to evaluate the impact of climate change on both meteorological and hydrological droughts, through the use of a generalization of the Standardized Precipitation Index (SPI). We use the Standardized Flow Index (SFI) to assess the hydrological drought, using flow time series instead of rainfall time series. In the case of the meteorological droughts, the Standardized Precipitation and Evapotranspiration Index (SPEI) has been applied to assess the variability of temperature impacts. In order to characterize climate change impacts on droughts, we have used projections from the CORDEX project (Coordinated Regional Climate Downscaling Experiment). Future rainfall and temperature time series for short (2011-2040) and medium terms (2041-2070) were obtained, applying a quantile mapping method to correct the bias of these time series. Regarding the hydrological drought, the Témez hydrological model has been applied to simulate the impacts of future temperature and rainfall time series on runoff and river discharges. It is a conceptual, lumped and a few parameters hydrological model. Nevertheless, it is necessary to point out the time difference between the meteorological and the hydrological droughts. The case study is the Jucar river basin (Spain), a highly regulated system with a share of 80% of water use for irrigated agriculture. The results show that the climate change would increase the historical drought impacts in the river basin. Acknowledgments The study has been supported by the IMPADAPT project (CGL2013-48424-C2-1-R) with Spanish MINECO (Ministerio de Economía y Competitividad) and European FEDER funds.

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

USDA-ARS?s Scientific Manuscript database

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

Summer drought predictability over Europe: empirical versus dynamical forecasts

NASA Astrophysics Data System (ADS)

Turco, Marco; Ceglar, Andrej; Prodhomme, Chloé; Soret, Albert; Toreti, Andrea; Doblas-Reyes Francisco, J.

2017-08-01

Seasonal climate forecasts could be an important planning tool for farmers, government and insurance companies that can lead to better and timely management of seasonal climate risks. However, climate seasonal forecasts are often under-used, because potential users are not well aware of the capabilities and limitations of these products. This study aims at assessing the merits and caveats of a statistical empirical method, the ensemble streamflow prediction system (ESP, an ensemble based on reordering historical data) and an operational dynamical forecast system, the European Centre for Medium-Range Weather Forecasts—System 4 (S4) in predicting summer drought in Europe. Droughts are defined using the Standardized Precipitation Evapotranspiration Index for the month of August integrated over 6 months. Both systems show useful and mostly comparable deterministic skill. We argue that this source of predictability is mostly attributable to the observed initial conditions. S4 shows only higher skill in terms of ability to probabilistically identify drought occurrence. Thus, currently, both approaches provide useful information and ESP represents a computationally fast alternative to dynamical prediction applications for drought prediction.

Estimating drought risk across Europe from reported drought impacts, hazard indicators and vulnerability factors

NASA Astrophysics Data System (ADS)

Blauhut, V.; Stahl, K.; Stagge, J. H.; Tallaksen, L. M.; De Stefano, L.; Vogt, J.

2015-12-01

Drought is one of the most costly natural hazards in Europe. Due to its complexity, drought risk, the combination of the natural hazard and societal vulnerability, is difficult to define and challenging to detect and predict, as the impacts of drought are very diverse, covering the breadth of socioeconomic and environmental systems. Pan-European maps of drought risk could inform the elaboration of guidelines and policies to address its documented severity and impact across borders. This work (1) tests the capability of commonly applied hazard indicators and vulnerability factors to predict annual drought impact occurrence for different sectors and macro regions in Europe and (2) combines information on past drought impacts, drought hazard indicators, and vulnerability factors into estimates of drought risk at the pan-European scale. This "hybrid approach" bridges the gap between traditional vulnerability assessment and probabilistic impact forecast in a statistical modelling framework. Multivariable logistic regression was applied to predict the likelihood of impact occurrence on an annual basis for particular impact categories and European macro regions. The results indicate sector- and macro region specific sensitivities of hazard indicators, with the Standardised Precipitation Evapotranspiration Index for a twelve month aggregation period (SPEI-12) as the overall best hazard predictor. Vulnerability factors have only limited ability to predict drought impacts as single predictor, with information about landuse and water resources as best vulnerability-based predictors. (3) The application of the "hybrid approach" revealed strong regional (NUTS combo level) and sector specific differences in drought risk across Europe. The majority of best predictor combinations rely on a combination of SPEI for shorter and longer aggregation periods, and a combination of information on landuse and water resources. The added value of integrating regional vulnerability information with drought risk prediction could be proven. Thus, the study contributes to the overall understanding of drivers of drought impacts, current practice of drought indicators selection for specific application, and drought risk assessment.

On the role of rising global temperatures on 2015-2016 Caribbean drought

NASA Astrophysics Data System (ADS)

Herrera, D. A.; Ault, T.

2016-12-01

In 2015 the Caribbean faced one of the worst droughts ever recorded. On some islands, like Cuba, the event represents the worst in over 100 years. Although this exceptional drought has been linked primarily to the recent El Niño, it is unclear whether its severity could have been enhanced by anthropogenic climate change. In this work, an analysis of the role played by anthropogenic warming on the 2015-2016 drought in the Caribbean is presented, using high-resolution drought datasets based on the self-calibrated Palmer Drought Severity Index (scPDSI), with the Penman-Monteith approximation of evapotranspiration. This effort further uses statistically-downscaled reanalysis products that span 1950 to the near present to establish an historical baseline for characterizing and monitoring drought in real time. The relative contribution of global warming is estimated by comparing the scPDSI calculated using detrended temperatures, against the scPDSI computed with the observed trend while holding all other terms at their historical or climatological values. Results indicate that during 2015, 70% of the Caribbean was affected by mild drought (-2 to -3 scPDSI units), 43% by moderate drought (-4 to -3) and 14% by severe drought (<-4). Consequently, this event was the most regionally-widespread since at least 1950. In contrast, during the 1997 drought, 47% of the region was under mild drought, 25% moderate drought and 8% severe drought. The approximate relative contribution of warmth on the 2015-2016 event varies substantially along the Caribbean, ranging from 8-12% in Puerto Rico and Lesser Antilles, to 14-29 % in Cuba and the Hispaniola Island. The inherent insular nature of the Caribbean island make them especially vulnerable to drought because water cannot be collected, moved, and stored on large spatial scales, like it can in the US Southwest. These results underscore the likely role climate change is playing in exacerbating regional drought impacts by favoring higher evapotranspiration rates from higher temperatures, and hence greater moisture losses during anomalous dry periods.

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

NASA Astrophysics Data System (ADS)

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

2012-12-01

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

Regional vegetation die-off in response to global-change-type drought

USGS Publications Warehouse

Breshears, D.D.; Cobb, N.S.; Rich, P.M.; Price, K.P.; Allen, Craig D.; Balice, R.G.; Romme, W.H.; Kastens, J.H.; Floyd, M. Lisa; Belnap, J.; Anderson, J.J.; Myers, O.B.; Meyer, Clifton W.

2005-01-01

Future drought is projected to occur under warmer temperature conditions as climate change progresses, referred to here as global-change-type drought, yet quantitative assessments of the triggers and potential extent of drought-induced vegetation die-off remain pivotal uncertainties in assessing climate-change impacts. Of particular concern is regional-scale mortality of overstory trees, which rapidly alters ecosystem type, associated ecosystem properties, and land surface conditions for decades. Here, we quantify regional-scale vegetation die-off across southwestern North American woodlands in 2002-2003 in response to drought and associated bark beetle infestations. At an intensively studied site within the region, we quantified that after 15 months of depleted soil water content, >90% of the dominant, overstory tree species (Pinus edulis, a piñon) died. The die-off was reflected in changes in a remotely sensed index of vegetation greenness (Normalized Difference Vegetation Index), not only at the intensively studied site but also across the region, extending over 12,000 km2 or more; aerial and field surveys confirmed the general extent of the die-off. Notably, the recent drought was warmer than the previous subcontinental drought of the 1950s. The limited, available observations suggest that die-off from the recent drought was more extensive than that from the previous drought, extending into wetter sites within the tree species' distribution. Our results quantify a trigger leading to rapid, drought-induced die-off of overstory woody plants at subcontinental scale and highlight the potential for such die-off to be more severe and extensive for future global-change-type drought under warmer conditions.

Regional vegetation die-off in response to global-change-type drought

PubMed Central

Breshears, David D.; Cobb, Neil S.; Rich, Paul M.; Price, Kevin P.; Allen, Craig D.; Balice, Randy G.; Romme, William H.; Kastens, Jude H.; Floyd, M. Lisa; Belnap, Jayne; Anderson, Jesse J.; Myers, Orrin B.; Meyer, Clifton W.

2005-01-01

Future drought is projected to occur under warmer temperature conditions as climate change progresses, referred to here as global-change-type drought, yet quantitative assessments of the triggers and potential extent of drought-induced vegetation die-off remain pivotal uncertainties in assessing climate-change impacts. Of particular concern is regional-scale mortality of overstory trees, which rapidly alters ecosystem type, associated ecosystem properties, and land surface conditions for decades. Here, we quantify regional-scale vegetation die-off across southwestern North American woodlands in 2002-2003 in response to drought and associated bark beetle infestations. At an intensively studied site within the region, we quantified that after 15 months of depleted soil water content, >90% of the dominant, overstory tree species (Pinus edulis, a piñon) died. The die-off was reflected in changes in a remotely sensed index of vegetation greenness (Normalized Difference Vegetation Index), not only at the intensively studied site but also across the region, extending over 12,000 km2 or more; aerial and field surveys confirmed the general extent of the die-off. Notably, the recent drought was warmer than the previous subcontinental drought of the 1950s. The limited, available observations suggest that die-off from the recent drought was more extensive than that from the previous drought, extending into wetter sites within the tree species' distribution. Our results quantify a trigger leading to rapid, drought-induced die-off of overstory woody plants at subcontinental scale and highlight the potential for such die-off to be more severe and extensive for future global-change-type drought under warmer conditions. PMID:16217022

Drought vulnerability assessment for prioritising drought warning implementation

NASA Astrophysics Data System (ADS)

Naumann, Gustavo; Faneca Sànchez, Marta; Mwangi, Emmah; Barbosa, Paulo; Iglesias, Ana; Garrote, Luis; Werner, Micha

2014-05-01

Drought warning provides a potentially efficient approach to mitigation of drought impacts, and should be targeted at areas most vulnerable to being adversely impacted. Assessing drought vulnerability is, however, complex and needs to consider susceptibility to drought impact as well as the capacity to cope with drought. In this paper a Drought Vulnerability Index (DVI) is proposed that considers four primary components that reflect the capacity of society to adapt to drought; the renewable natural capital, the economic capacity, the human and civic resources, and the available infrastructure and technology. The DVI is established as a weighted combination of these four components, each a composite of selected indicators. Constituent indicators are calculated based on national and/or regional census data and statistics, and while the resulting DVI should not be considered an absolute measure of drought vulnerability it does provide for a prioritisation of areas that can be used to target drought warning efforts. Sensitivity analysis of weights applied show the established DVI to be robust. Through the DVI the development of drought forecasting and warning can be targeted at the most vulnerable areas. The proposed DVI is applied at both the continental scale in Africa to assess drought vulnerability of the different nations across Africa, and at the national level in Kenya, allowing for prioritisation of the counties within Kenya to drought vulnerability. Results show the relative vulnerability of countries and counties vulnerable to drought. At the continental scale, Somalia, Burundi, Niger, Ethiopia, Mali and Chad are found to be the countries most vulnerable to drought. At the national level, the relative vulnerability of the counties across Kenya is found, with counties in the North-East of Kenya having the highest values of DVI. At the country level results were compared with drought disaster information from the EM-DAT disaster database, showing a good agreement between recorded drought impact and the established DVI classes. Kenya counties most vulnerable to drought are primarily located in the North-East of the country, showing a reasonable agreement with the spatial distribution of impacts of the 2010/2011 drought, despite the drought itself being more widespread.

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.

Estimating Drought Thresholds for Wheat in the Canadian Prairies Using Remote Sensing Products

NASA Astrophysics Data System (ADS)

Munoz Hernandez, A.

2013-12-01

Droughts affect millions of people around the world, and depending on their duration and intensity, crops, cattle, and ecosystems can be decimated. One of the most susceptible economic sectors to drought is agriculture. Planners in the agricultural sector understand that drought conditions translate into lower yields, and subsequently reduced profits, but the relationship between drought thresholds and economic impacts remain unclear. This project focuses on estimating the Standardized Precipitation Index (SPI) for the Palliser Triangle to develop an understanding of the relationship between droughts and economic impacts on the production of wheat. The Palliser Triangle is a semi-arid region that experiences severe episodic droughts and is located primarily within two provinces: Alberta and Saskatchewan. The region supports a variety of crops including grains, oilseed, and forage crops, but predominantly wheat. The SPI is a probability index based entirely on precipitation deficits that identifies drought conditions with negative values and wet conditions using positive values. For this project, the SPI was estimated on a monthly basis for a period of thirty-four years utilizing precipitation data from the North American Land Data Assimilation Systems (NDLAS) with a resolution of 1/8 degrees. Agricultural data was collected from Statistics Canada, Agriculture Division on a yearly basis for each agricultural district located within the study area. The SPI estimated values were compared against the yield reduction of wheat for a period of thirty years using statistical linear regression. The combination of highest r-squared and lowest standard error was selected. The use of remote sensing products in Canada is optimal since the in-situ measurement networks are very sparse. However, selecting the appropriate satellite products is challenging. The Tropical Rainfall Measuring Mission (TRMM) has been successfully used to improve the understanding of precipitation within the tropics since the satellite was launched. However, the spatial coverage excludes Canada. On the other hand, the information provided by the Global Precipitation Climatology Project (GPCP) covers the study area, but the resolution is too coarse to establish relationships between drought and agriculture at the district level. Therefore, there is a need of a Global Precipitation Mission that collects data for the globe at a fine resolution that in combination with existing precipitation products allows the estimation of the SPI, among other drought indicators, in a near-real time.

Identification of novel drought-tolerant-associated SNPs in common bean (Phaseolus vulgaris)

PubMed Central

Villordo-Pineda, Emiliano; González-Chavira, Mario M.; Giraldo-Carbajo, Patricia; Acosta-Gallegos, Jorge A.; Caballero-Pérez, Juan

2015-01-01

Common bean (Phaseolus vulgaris L.) is a leguminous in high demand for human nutrition and a very important agricultural product. Production of common bean is constrained by environmental stresses such as drought. Although conventional plant selection has been used to increase production yield and stress tolerance, drought tolerance selection based on phenotype is complicated by associated physiological, anatomical, cellular, biochemical, and molecular changes. These changes are modulated by differential gene expression. A common method to identify genes associated with phenotypes of interest is the characterization of Single Nucleotide Polymorphims (SNPs) to link them to specific functions. In this work, we selected two drought-tolerant parental lines from Mesoamerica, Pinto Villa, and Pinto Saltillo. The parental lines were used to generate a population of 282 families (F3:5) and characterized by 169 SNPs. We associated the segregation of the molecular markers in our population with phenotypes including flowering time, physiological maturity, reproductive period, plant, seed and total biomass, reuse index, seed yield, weight of 100 seeds, and harvest index in three cultivation cycles. We observed 83 SNPs with significant association (p < 0.0003 after Bonferroni correction) with our quantified phenotypes. Phenotypes most associated were days to flowering and seed biomass with 58 and 44 associated SNPs, respectively. Thirty-seven out of the 83 SNPs were annotated to a gene with a potential function related to drought tolerance or relevant molecular/biochemical functions. Some SNPs such as SNP28 and SNP128 are related to starch biosynthesis, a common osmotic protector; and SNP18 is related to proline biosynthesis, another well-known osmotic protector. PMID:26257755

Identification of novel drought-tolerant-associated SNPs in common bean (Phaseolus vulgaris).

PubMed

Villordo-Pineda, Emiliano; González-Chavira, Mario M; Giraldo-Carbajo, Patricia; Acosta-Gallegos, Jorge A; Caballero-Pérez, Juan

2015-01-01

Common bean (Phaseolus vulgaris L.) is a leguminous in high demand for human nutrition and a very important agricultural product. Production of common bean is constrained by environmental stresses such as drought. Although conventional plant selection has been used to increase production yield and stress tolerance, drought tolerance selection based on phenotype is complicated by associated physiological, anatomical, cellular, biochemical, and molecular changes. These changes are modulated by differential gene expression. A common method to identify genes associated with phenotypes of interest is the characterization of Single Nucleotide Polymorphims (SNPs) to link them to specific functions. In this work, we selected two drought-tolerant parental lines from Mesoamerica, Pinto Villa, and Pinto Saltillo. The parental lines were used to generate a population of 282 families (F3:5) and characterized by 169 SNPs. We associated the segregation of the molecular markers in our population with phenotypes including flowering time, physiological maturity, reproductive period, plant, seed and total biomass, reuse index, seed yield, weight of 100 seeds, and harvest index in three cultivation cycles. We observed 83 SNPs with significant association (p < 0.0003 after Bonferroni correction) with our quantified phenotypes. Phenotypes most associated were days to flowering and seed biomass with 58 and 44 associated SNPs, respectively. Thirty-seven out of the 83 SNPs were annotated to a gene with a potential function related to drought tolerance or relevant molecular/biochemical functions. Some SNPs such as SNP28 and SNP128 are related to starch biosynthesis, a common osmotic protector; and SNP18 is related to proline biosynthesis, another well-known osmotic protector.

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

NASA Astrophysics Data System (ADS)

Ziolkowska, J. R.; Reyes, R.

2016-12-01

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

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.

Attribution of Disturbances Causing Tree Mortality for the Continental U.S.

NASA Astrophysics Data System (ADS)

Wang, M.; Xu, C.; Allen, C. D.; McDowell, N. G.

2016-12-01

Broad-scale tree mortality has been frequently reported and documented to increase with warming climate and human activities. However, there is so far no general method to quantify the relative contributions of different disturbances on observed broad-scale tree mortality. In this study, we presented a framework to investigate the contribution of various disturbances causing tree mortality for 2000-2014 in the continental US. Our work is based on the high-resolution forest-loss data developed by Hansen et al. (2013). Firstly, fire-driven mortality was determined using the data from Monitoring Trends in Burn Severity (MTBS) project. Secondly, a landscape-pattern-recognition approach focusing on the differences of boundary complexity caused by natural and anthropogenic disturbances was developed to attribute harvest-driven mortality patches. Then, a drought threshold was determined through conducting an intensive literature survey for attribution of drought-driven mortality. Our results showed that we can correctly attribute 85% harvest-driven mortality as compared to Forest Inventory and Analysis (FIA) data. Based on Evaporative Stress Index (ESI), our literature survey suggests that most mortality events happened at extreme drought (37.7%), then severe (31.4%) and moderate (23.4%) drought. In total, 92.6% of drought-induced mortality events observed during 2000-2014 occurred at drought conditions of moderate or worse with corresponding ESI values ranging from -0.9 -2.49. Therefore, -0.9 will be used as the threshold to attribute drought-driven tree mortality. Overall, these results imply a great potential for using these methods to identify and attribute disturbances driving tree death at broad spatial scales.

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

NASA Astrophysics Data System (ADS)

Kogan, F.

2012-12-01

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

Spatiotemporal trends in mean temperatures and aridity index over Rwanda

NASA Astrophysics Data System (ADS)

Muhire, I.; Ahmed, F.

2016-01-01

This study aims at quantifying the trends in mean temperatures and aridity index over Rwanda for the period of 1961-1992, based on analysis of climatic data (temperatures, precipitations, and potential evapotranspiration). The analysis of magnitude and significance of trends in temperatures and aridity index show the degree of climate change and mark the level of vulnerability to extreme events (e.g., droughts) in different areas of the country. The study reveals that mean temperatures increased in most parts of the country, with a significant increase observed in the eastern lowlands and in the southwestern parts. The highlands located in the northwest and the Congo-Nile crest showed a nonsignificant increase in mean temperatures. Aridity index increased only in March, April, October, and November, corresponding with the rainy seasons. The remaining months of the year showed a decreasing trend. At an annual resolution, the highlands and the western region showed a rise in aridity index with a decreasing pattern over the eastern lowlands and the central plateau. Generally, the highlands presented a nonsignificant increase in mean temperatures and aridity index especially during the rainy seasons. The eastern lowlands showed a significant increase in mean temperatures and decreasing trends in aridity index. Therefore, these areas are bound to experience more droughts, leading to reduced water and consequent decline in agricultural production. On the other hand, the north highlands and southwest region will continue to be more productive.

Statistical properties of effective drought index (EDI) for Seoul, Busan, Daegu, Mokpo in South Korea

NASA Astrophysics Data System (ADS)

Park, Jong-Hyeok; Kim, Ki-Beom; Chang, Heon-Young

2014-08-01

Time series of drought indices has been considered mostly in view of temporal and spatial distributions of a drought index so far. Here we investigate the statistical properties of a daily Effective Drought Index (EDI) itself for Seoul, Busan, Daegu, Mokpo for the period of 100 years from 1913 to 2012. We have found that both in dry and wet seasons the distribution of EDI as a function of EDI follows the Gaussian function. In dry season the shape of the Gaussian function is characteristically broader than that in wet seasons. The total number of drought days during the period we have analyzed is related both to the mean value and more importantly to the standard deviation. We have also found that according to the distribution of the number of occasions where the EDI values of several consecutive days are all less than a threshold, the distribution follows the exponential distribution. The slope of the best fit becomes steeper not only as the critical EDI value becomes more negative but also as the number of consecutive days increases. The slope of the exponential distribution becomes steeper as the number of the city in which EDI is simultaneously less than a critical EDI in a row increases. Finally, we conclude by pointing out implications of our findings.

Assessing and mapping drought hazard in Africa and South-Central America with a Meteorological Drought Severity Index

NASA Astrophysics Data System (ADS)

Carrao, Hugo; Barbosa, Paulo; Vogt, Jürgen

2015-04-01

Drought is a recurring extreme climate event characterized by a temporary deficit of precipitation, soil moisture, streamflow, or any combination of the three taking place at the same time. The immediate consequences of short-term (i.e. a few weeks duration) droughts are, for example, a fall in crop production, poor pasture growth and a decline in fodder supplies from crop residues, whereas prolonged water shortages (e.g. of several months or years duration) may, amongst others, lead to a reduction in hydro-electrical power production and an increase of forest fires. As a result, comprehensive drought risk management is nowadays critical for many regions in the world. Examples are many African and South-and Central American countries that strongly depend on rain-fed agriculture for economic development with hydroelectricity and biomass as main sources of energy. Drought risk is the probability of harmful consequences, or expected losses resulting from interactions between drought hazard, i.e. the physical nature of droughts, and the degree to which a population or activity is vulnerable to its effects. As vulnerability to drought is increasing globally and certain tasks, such as distributive policies (e.g. relief aid, regulatory exemptions, or preparedness investments), require information on drought severity that is comparable across different climatic regions, greater attention has recently been directed to the development of methods for a standardized quantification of drought hazard. In this study we, therefore, concentrate on a methodology for assessing the severity of historical droughts and on mapping the frequency of their occurrence. To achieve these goals, we use a new Meteorological Drought Severity Index (MDSI). The motivation is twofold: 1) the observation that primitive indices of drought severity directly measure local precipitation shortages and cannot be compared geographically; and that 2) standardized indices of drought do not take into account the intra-annual variability of precipitation in estimating the severity of events that can impact on seasonal activities. The MDSI is standardized in space and time, and considers the relative monthly precipitation deficits and the seasonal influence of precipitation regimes in the meteorological drought severity computation. In this study, the calculation of the MDSI is performed with monthly precipitation totals from the Full Data Reanalysis Monthly Product Version 6.0 of the Global Precipitation Climatology Centre (GPCC). This dataset provides a global analysis at 0.5 dd latitude/longitude grid spacing of monthly precipitation over land from operational in situ rain gauges collected between January 1901 and December 2010. Using the MDSI, we estimated the severity of drought events that occurred in the past 100 years in Africa and South-Central America, and produced drought hazard maps based on the probability of exceedance the median historical severity. Overall, results indicate that drought hazard is high for semiarid areas, such as Northeastern and Southern South America, as well as Eastern and Southwestern Africa. Since available water resources in semiarid areas are already insufficient to permanently meet the demands of human activities, the outcomes highlight the aggravated risk for food security and confirm the need for the implementation of disaster mitigation measures in those regions.

A comprehensively quantitative method of evaluating the impact of drought on crop yield using daily multi-scale SPEI and crop growth process model.

PubMed

Wang, Qianfeng; Wu, Jianjun; Li, Xiaohan; Zhou, Hongkui; Yang, Jianhua; Geng, Guangpo; An, Xueli; Liu, Leizhen; Tang, Zhenghong

2017-04-01

The quantitative evaluation of the impact of drought on crop yield is one of the most important aspects in agricultural water resource management. To assess the impact of drought on wheat yield, the Environmental Policy Integrated Climate (EPIC) crop growth model and daily Standardized Precipitation Evapotranspiration Index (SPEI), which is based on daily meteorological data, are adopted in the Huang Huai Hai Plain. The winter wheat crop yields are estimated at 28 stations, after calibrating the cultivar coefficients based on the experimental site data, and SPEI data was taken 11 times across the growth season from 1981 to 2010. The relationship between estimated yield and multi-scale SPEI were analyzed. The optimum time scale SPEI to monitor drought during the crop growth period was determined. The reference yield was determined by averaging the yields from numerous non-drought years. From this data, we propose a comprehensive quantitative method which can be used to predict the impact of drought on wheat yields by combining the daily multi-scale SPEI and crop growth process model. This method was tested in the Huang Huai Hai Plain. The results suggested that estimation of calibrated EPIC was a good predictor of crop yield in the Huang Huai Hai Plain, with lower RMSE (15.4 %) between estimated yield and observed yield at six agrometeorological stations. The soil moisture at planting time was affected by the precipitation and evapotranspiration during the previous 90 days (about 3 months) in the Huang Huai Hai Plain. SPEI G90 was adopted as the optimum time scale SPEI to identify the drought and non-drought years, and identified a drought year in 2000. The water deficit in the year 2000 was significant, and the rate of crop yield reduction did not completely correspond with the volume of water deficit. Our proposed comprehensive method which quantitatively evaluates the impact of drought on crop yield is reliable. The results of this study further our understanding why the adoption of counter measures against drought is important and direct farmers to choose drought-resistant crops.

Relationship between crown dieback and drought in the southeastern United States

Treesearch

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

2012-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Connections between meteorological and hydrological droughts in a semi-arid basin of the middle Yellow River

NASA Astrophysics Data System (ADS)

Li, Binquan; Zhu, Changchang; Liang, Zhongmin; Wang, Guoqing; Zhang, Yu

2018-06-01

Differences between meteorological and hydrological droughts could reflect the regional water consumption by both natural elements and human water-use. The connections between these two drought types were analyzed using the Standardized Precipitation Evapotranspiration Index (SPEI) and Standardized Streamflow Index (SSI), respectively. In a typical semi-arid basin of the middle Yellow River (Qingjianhe River basin), annual precipitation and air temperature showed significantly downward and upward trends, respectively, with the rates of -2.37 mm yr-1 and 0.03 °C yr-1 (1961-2007). Under their synthetic effects, water balance variable (represented by SPEI) showed obviously downward (drying) trend at both upstream and whole basin areas. For the spatial variability of precipitation, air temperature and the calculated SPEI, both upstream and downstream areas experienced very similar change characteristics. Results also suggested that the Qingjianhe River basin experienced near normal condition during the study period. As a whole, this semi-arid basin mainly had the meteorological drought episodes in the mid-1960s, late-1990s and the 2000s depicted by 12-month SPEI. The drying trend could also be depicted by the hydrological drought index (12-month SSI) at both upstream and downstream stations (Zichang and Yanchuan), but the decreasing trends were not significant. A correlation analysis showed that hydrological system responds rapidly to the change of meteorological conditions in this semi-arid region. This finding could be an useful implication to drought research for those semi-arid basins with intensive human activities.

Evaluation of a Model-Based Groundwater Drought Indicator in the Conterminous U.S.

NASA Technical Reports Server (NTRS)

Li, Bailing; Rodell, Matthew

2015-01-01

Monitoring groundwater drought using land surface models is a valuable alternative given the current lack of systematic in situ measurements at continental and global scales and the low resolution of current remote sensing based groundwater data. However, uncertainties inherent to land surface models may impede drought detection, and thus should be assessed using independent data sources. In this study, we evaluated a groundwater drought index (GWI) derived from monthly groundwater storage output from the Catchment Land Surface Model (CLSM) using a GWI similarly derived from in situ groundwater observations. Groundwater observations were obtained from unconfined or semi-confined aquifers in eight regions of the central and northeastern U.S. Regional average GWI derived from CLSM exhibited strong correlation with that from observation wells, with correlation coefficients between 0.43 and 0.92. GWI from both in situ data and CLSM was generally better correlated with the Standard Precipitation Index (SPI) at 12 and 24 month timescales than at shorter timescales, but it varied depending on climate conditions. The correlation between CLSM derived GWI and SPI generally decreases with increasing depth to the water table, which in turn depends on both bedrock depth (a CLSM parameter) and mean annual precipitation. The persistence of CLSM derived GWI is spatially varied and again shows a strong influence of depth to groundwater. CLSM derived GWI generally persists longer than GWI derived from in situ data, due at least in part to the inability of coarse model inputs to capture high frequency meteorological variability at local scales. The study also showed that groundwater can have a significant impact on soil moisture persistence where the water table is shallow. Soil moisture persistence was estimated to be longer in the eastern U.S. than in the west, in contrast to previous findings that were based on models that did not represent groundwater. Assimilation of terrestrial water storage data from the Gravity Recovery and Climate Experiment (GRACE) satellite mission improved the correlation between CLSM based regional average GWI and that based on in situ data in six of the eight regions. Practical issues regarding the application of GRACE assimilated groundwater storage for drought detection are discussed. An important conclusion of this study is that model parameters that control the depth to the water table, including bedrock depth, strongly influence the evolution and persistence of simulated groundwater and require careful configuration for drought monitoring.

Combined role of heat and water stresses on wheat, maize and rice inter-annual variability and trend from 1980 to 2010.

NASA Astrophysics Data System (ADS)

Zampieri, M.; Ceglar, A., , Dr; Dentener, F., , Dr; van den Berg, M., , Dr; Toreti, A., , Dr

2017-12-01

Heat waves and drought are often considered the most damaging climatic stressors for wheat and maize. In this study, based on data derived from observations, we characterize and attribute the effects of these climate extremes on wheat and maize yield anomalies (at global and national scales) with respect to the mean trend from 1980 to 2010. Using a combination of up-to-date heat wave and drought indexes (i.e. the Heat Magnitude Day, HMD, and the Standardized Precipitation Evapotranspiration Index, SPEI), we have developed a composite indicator (i.e. the Combined Stress Index, CSI) that is able to capture the spatio-temporal characteristics of the underlying physical processes in the different agro-climatic regions of the world. At the global level, our diagnostic explains the 42% and the 50% of the inter-annual wheat and maize production variabilities, respectively. The relative importance of heat stress and drought in determining the yield anomalies depends on the region. Compared to maize, and in contrast to common perception, water excess affects wheat production more than drought in several countries. The index definition can be modified in order to quantify the role of combined heat and water stress events occurrence in determining the recorded yield trends as well. Climate change is increasingly limiting maize yields in several countries, especially in Europe and China. A comparable opposite signal, albeit less statistically significant, is found for the USA, which is the main world producer. As for rice, we provide a statistical evidence pointing out to the importance of considering the interactions with the horizontal surface waters fluxes carried out by the rivers. In fact, compared to wheat and maize, the CSI statistical skills in explaining rice production variability are quite reduced. This issue is particularly relevant in paddy fields and flooded lowlands where rice is mainly grown. Therefore, we have modified the procedure including a proxy for the surface freshwater availability i.e. the Standardized River Discharge Index (SRDI), defined in this study. The modified CSI explains the 35% of the global rice production inter-annual anomalies.

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. This paper concludes by exploring the potential of replicating such a partnership approach to climate risk assessment in other regions. Authors of the paper: Surminski, Swenja (London School of Economics); Holt Andersen, Birgitte (CWare); Hohl, Roman (Swiss Re); Andersen, Søren (COWI)

Dzuds, droughts, and livestock mortality in Mongolia

NASA Astrophysics Data System (ADS)

Palat Rao, Mukund; Davi, Nicole K.; D'Arrigo, Rosanne D.; Skees, Jerry; Nachin, Baatarbileg; Leland, Caroline; Lyon, Bradfield; Wang, Shih-Yu; Byambasuren, Oyunsanaa

2015-07-01

Recent incidences of mass livestock mortality, known as dzud, have called into question the sustainability of pastoral nomadic herding, the cornerstone of Mongolian culture. A total of 20 million head of livestock perished in the mortality events of 2000-2002, and 2009-2010. To mitigate the effects of such events on the lives of herders, international agencies such as the World Bank are taking increasing interest in developing tailored market-based solutions like index-insurance. Their ultimate success depends on understanding the historical context and underlying causes of mortality. In this paper we examine mortality in 21 Mongolian aimags (provinces) between 1955 and 2013 in order to explain its density independent cause(s) related to climate variability. We show that livestock mortality is most strongly linked to winter (November-February) temperatures, with incidences of mass mortality being most likely to occur because of an anomalously cold winter. Additionally, we find prior summer (July-September) drought and precipitation deficit to be important triggers for mortality that intensifies the effect of upcoming winter temperatures on livestock. Our density independent mortality model based on winter temperature, summer drought, summer precipitation, and summer potential evaporanspiration explains 48.4% of the total variability in the mortality dataset. The Mongolian index based livestock insurance program uses a threshold of 6% mortality to trigger payouts. We find that on average for Mongolia, the probability of exceedance of 6% mortality in any given year is 26% over the 59 year period between 1955 and 2013.

Impacts of droughts on carbon sequestration by China's terrestrial ecosystems from 2000 to 2011

NASA Astrophysics Data System (ADS)

Liu, Y. B.; Zhou, Y. L.; Ju, W. M.; Wang, S. Q.; Wu, X. C.; He, M. Z.

2013-11-01

In recent years, droughts have frequently hit China's terrestrial ecosystems. How these droughts affected carbon sequestration by China's terrestrial ecosystems is still unclear. In this study, the process-based Boreal Ecosystem Productivity Simulator (BEPS) model, driven by remotely sensed vegetation parameters, was employed to assess the effects of droughts on net ecosystem productivity (NEP) of terrestrial ecosystems in China for the period from 2000 to 2011. Different categories of droughts, as indicated by a standard precipitation index (SPI), extensively hit terrestrial ecosystems in China, particularly in 2001, 2006, 2009 and 2011. The national total NEP exhibited a slight decline of -11.3 Tg C yr-2 during the study period, mainly due to large reductions of NEP in typical drought-hit years 2001, 2006, 2009 and 2011, ranging from 61.1 Tg C yr-1 to 168.8 Tg C yr-1. National and regional total NEP anomalies were correlated with corresponding annual mean SPI, especially in Northwest China, North China, Central China, and Southwest China. In drought years, the reductions of NEP might be caused by a larger decrease in gross primary productivity (GPP) than in respiration (RE) (2001 and 2011), a decrease in GPP and an increase in RE (2009), or a larger increase in RE than in GPP (2006). Droughts had lagged effects of up to 3-6 months on NEP due to different reactions of GPP and RE to droughts. In east humid and warm parts of China, droughts have predominant and short-term lagged influences on NEP. In western cold and arid regions, the effects of droughts on NEP were relatively weaker and might last for a longer period of time.

Drought in West Africa: How CHIRPS and Reference Evapotranspiration can be used for Index Insurance in a Non-Stationary Setting

NASA Astrophysics Data System (ADS)

Blakeley, S. L.; Husak, G. J.; Harrison, L.; Funk, C. C.; Osgood, D. E.; Peterson, P.

2017-12-01

Index insurance is increasingly used as a safety net and productivity tool in order to improve the resilience of small-holder farmers in developing countries. In West Africa, there are already index insurance projects in many countries, and various non-governmental organizations are eager to expand implementation of this risk management tool. Often, index insurance payouts rely on rainfall to determine drought years, but designation of years based on precipitation variations is particularly complex in places like West Africa where precipitation is subject to much natural variability across timescales [Giannini 2003, among others]. Furthermore, farmers must also rely on other weather factors for good crop yields, such as the availability of moisture for their plants to absorb and maximum daily temperatures staying within an acceptable range for the crops. In this presentation, the payouts of an index based on rainfall (as measured by the Climate Hazards Group Infrared Precipitation with Stations {CHIRPS} dataset) is compared to the payouts of an index using reference evapotranspiration data (using the ASCE's Penmen-Monteith formula and MERRA-2 drivers). The West African rainfall index exhibits a fair amount of long-term variability, reflective of the Atlantic Multidecadal Oscillation, but the reference evapotranspiration index shows different variability, through changes in radiative forcing and temperatures. Therefore, the use of rainfall for an index is appropriate for capturing rainfall deficits, but reference evapotranspiration may also be an appropriate addition to an index or as a stand-alone index for capturing crop stress. In summary, the results point to farmer input as an invaluable source of knowledge in determining the most appropriate dataset as an index for crop insurance. Alessandra Giannini, R Saravanan, and P Chang. Oceanic forcing of Sahel rainfall on interannual to interdecadal time scales. Science, 302(5647):1027-1030, 2003.

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

NASA Astrophysics Data System (ADS)

Kuwayama, Y.; Bernknopf, R.; Brookshire, D.; Macauley, M.; Zaitchik, B. F.; Rodell, M.; Vail, P.; Thompson, A.

2015-12-01

In this project, we develop a framework to estimate the economic value of information from the Gravity and Climate Experiment (GRACE) for drought monitoring and to understand how the GRACE Data Assimilation (GRACE-DA) system can inform decision making to improve regional economic outcomes. Specifically, we consider the potential societal value of further incorporating GRACE-DA information into the U.S. Drought Monitor mapmaking process. Research activities include (a) a literature review, (b) a series of listening sessions with experts and stakeholders, (c) the development of a conceptual economic framework based on a Bayesian updating procedure, and (d) an econometric analysis and retrospective case study to understand the GRACE-DA contribution to agricultural policy and production decisions. Taken together, the results from these research activities support our conclusion that GRACE-DA has the potential to lower the variance associated with our understanding of drought and that this improved understanding has the potential to change policy decisions that lead to tangible societal benefits.

Drought - A Global Assessment

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

Climate Projections and Drought: Verification for the Colorado River Basin

NASA Astrophysics Data System (ADS)

Santos, N. I.; Piechota, T. C.; Miller, W. P.; Ahmad, S.

2017-12-01

The Colorado River Basin has experienced the driest 17 year period (2000-2016) in over 100 years of historical record keeping. While the Colorado River reservoir system began the current drought at near 100% capacity, reservoir storage has fallen to just above 50% during the drought. Even though federal and state water agencies have worked together to mitigate the impact of the drought and have collaboratively sponsored conservation programs and drought contingency plans, the 17-years of observed data beg the question as to whether the most recent climate projections would have been able to project the current drought's severity. The objective of this study is to analyze observations and ensemble projections (e.g. temperature, precipitation, streamflow) from the CMIP3 and CMIP5 archive in the Colorado River Basin and compare metrics related to skill scores, the Palmer Drought Severity Index, and water supply sustainability index. Furthermore, a sub-ensemble of CMIP3/CMIP5 projections, developed using a teleconnection replication verification technique developed by the author, will also be compared to the observed record to assist in further validating the technique as a usable process to increase skill in climatological projections. In the end, this study will assist to better inform water resource managers about the ability of climate ensembles to project hydroclimatic variability and the appearance of decadal drought periods.

Drought vulnerability assessment of maize in Sub-Saharan Africa: Insights from physical and social perspectives

NASA Astrophysics Data System (ADS)

Kamali, Bahareh; Abbaspour, Karim C.; Wehrli, Bernhard; Yang, Hong

2018-03-01

Drought as a slow-onset phenomenon inflicts important losses to agriculture where the degree of vulnerability depends not only on physical variables such as precipitation and temperature, but also on societal preparedness. While the scopes of physical and social vulnerability are very different in nature, studies distinguishing these two aspects have been lacking. In this study we address the physical and social aspects of drought vulnerability of maize (CDVIphy and CDVIsoc) in Sub-Saharan Africa (SSA). To quantify vulnerability, we applied a probabilistic framework combining a Drought Exposure Index (DEI) with a physical or social Crop Failure Index, CFIphy or CFIsoc, respectively. DEI was derived from the exceedance probability of precipitation. Maize yields, simulated using the Environmental Policy Integrated Climate (EPIC) model, were used to build CFIphy, whereas the residual of simulated and FAO recorded yields were used to construct CFIsoc. The results showed that southern and partially central Africa are more vulnerable to physical drought as compared to other regions. Central and western Africa, however, are socially highly vulnerable. Comparison of CDVIphy and CDVIsoc revealed that societal factors cause more vulnerability than physical variables in almost all SSA countries except Nigeria and South Africa. We conclude that quantification of both drought vulnerabilities help a better characterization of droughts and identify regions where more investments in drought preparedness are required.

Statistical trends of some meteorological drought indices in Europe

NASA Astrophysics Data System (ADS)

Diaz Loaiza, Andres; Roper, Aaron; Guimarães, Gabriela; Ward, Philip; Aerts, Jeroen

2017-04-01

Out of all the natural phenomena that afflict human society, droughts are one of the most damaging. Droughts have been estimated to cost an average of 6 to 8 billion dollars in damages per year, yet they are often overlooked in comparison to other natural disasters, because they are invisible to the naked eye, and quite difficult to measure. The presented research display a developed methodology to assess the behavior of different meteorological drought indices on a continental scale in Europe. Firstly, is assessed the behavior on varying temporal scales, and secondly, it is determine whether or not droughts have become more frequent and/or intense in recent decades. Results over the analyzed period (1950 to 2014), shows that the frequency of meteorological drought events are slightly increasing (in the SPEI index). Instead for the SPI index, this trend is not patent probably because of his own definition. About the intensity, in contrast, it seems the events are become more intense. A plausible conclusion is that the quantity of annually events of drought over Europe are conserved, but the same are becoming longer and intense. The findings of this research emphasize the impacts that climate change and increasing temperatures will have on drought impacts and the need for water management sectors to incorporate that knowledge into the consumption and protection of water resources. The advantage of using geospatial techniques into the drought monitoring, like the kriging interpolation used in the present model, allow us to comprehensively analyze drought events in different time and spatial scales.

Forecasting European Droughts using the North American Multi-Model Ensemble (NMME)

NASA Astrophysics Data System (ADS)

Thober, Stephan; Kumar, Rohini; Samaniego, Luis; Sheffield, Justin; Schäfer, David; Mai, Juliane

2015-04-01

Soil moisture droughts have the potential to diminish crop yields causing economic damage or even threatening the livelihood of societies. State-of-the-art drought forecasting systems incorporate seasonal meteorological forecasts to estimate future drought conditions. Meteorological forecasting skill (in particular that of precipitation), however, is limited to a few weeks because of the chaotic behaviour of the atmosphere. One of the most important challenges in drought forecasting is to understand how the uncertainty in the atmospheric forcings (e.g., precipitation and temperature) is further propagated into hydrologic variables such as soil moisture. The North American Multi-Model Ensemble (NMME) provides the latest collection of a multi-institutional seasonal forecasting ensemble for precipitation and temperature. In this study, we analyse the skill of NMME forecasts for predicting European drought events. The monthly NMME forecasts are downscaled to daily values to force the mesoscale hydrological model (mHM). The mHM soil moisture forecasts obtained with the forcings of the dynamical models are then compared against those obtained with the Ensemble Streamflow Prediction (ESP) approach. ESP recombines historical meteorological forcings to create a new ensemble forecast. Both forecasts are compared against reference soil moisture conditions obtained using observation based meteorological forcings. The study is conducted for the period from 1982 to 2009 and covers a large part of the Pan-European domain (10°W to 40°E and 35°N to 55°N). Results indicate that NMME forecasts are better at predicting the reference soil moisture variability as compared to ESP. For example, NMME explains 50% of the variability in contrast to only 31% by ESP at a six-month lead time. The Equitable Threat Skill Score (ETS), which combines the hit and false alarm rates, is analysed for drought events using a 0.2 threshold of a soil moisture percentile index. On average, the NMME based ensemble forecasts have consistently higher skill than the ESP based ones (ETS of 13% as compared to 5% at a six-month lead time). Additionally, the ETS ensemble spread of NMME forecasts is considerably narrower than that of ESP; the lower boundary of the NMME ensemble spread coincides most of the time with the ensemble median of ESP. Among the NMME models, NCEP-CFSv2 outperforms the other models in terms of ETS most of the time. Removing the three worst performing models does not deteriorate the ensemble performance (neither in skill nor in spread), but would substantially reduce the computational resources required in an operational forecasting system. For major European drought events (e.g., 1990, 1992, 2003, and 2007), NMME forecasts tend to underestimate area under drought and drought magnitude during times of drought development. During drought recovery, this underestimation is weaker for area under drought or even reversed into an overestimation for drought magnitude. This indicates that the NMME models are too wet during drought development and too dry during drought recovery. In summary, soil moisture drought forecasts by NMME are more skillful than those of an ESP based approach. However, they still show systematic biases in reproducing the observed drought dynamics during drought development and recovery.

Reverse relationship between drought of mid-latitudes in East Asia and Northwest Pacific tropical cyclone genesis frequency in summer

NASA Astrophysics Data System (ADS)

Choi, Jae-Won; Cha, Yumi; Kim, Jeoung-Yun

2016-12-01

This study found that there is a significant negative correlation between summer drought in Korea, China and Japan and the frequency of tropical cyclone (TC) in the subtropical western North Pacific (SWNP) using effective drought index (EDI). The frequency of TCs that affect Korea is low (high) in a year of summer drought (non-drought). As a case study, in 1994 when there is extremely severe summer drought in Korea, there was high frequency of TCs while in 2003 when there was least severe summer drought, the frequency of TCs is the lowest. Changes in the anomalous secondary circulation, namely anomalous upward (downward) flow in the SWNP and anomalous downward (upward) flow in the mid-latitudes of East Asia, are one of the causes of drought (non-drought).

The SPEIbase: a new gridded product for the analysis of drought variability and drought impacts

NASA Astrophysics Data System (ADS)

Begueria-Portugues, S.; Vicente-Serrano, S. M.; López-Moreno, J. I.; Angulo-Martínez, M.; El Kenawy, A.

2010-09-01

Recently a new drought indicator, the Standardised Precipitation-Evapotranspiration Index (SPEI), has been proposed to quantify the drought condition over a given area. The SPEI considers not only precipitation but also evapotranspiration (PET) data on its calculation, allowing for a more complete approach to explore the effects of climate change on drought conditions. The SPEI can be calculated at several time scales to adapt to the characteristic times of response to drought of target natural and economic systems, allowing determining their resistance to drought. Following the formulation of the SPEI a global dataset, the SPEIbase, has been made available to the scientific community. The dataset covers the period 1901-2006 with a monthly frequency, and offers global coverage at a 0.5 degrees resolution. The dataset consists on the monthly values of the SPEI at the time scales from 1 to 48 months. A description of the data and metadata, and links to download the files, are provided at http://sac.csic.es/spei. On this communication we will detail the methodology for computing the SPEI and the characteristics of the SPEIbase. A thorough discussion of the SPEI index, and some examples of use, will be provided in a companion comunication.

(How) Can We Use Satellite Data to Estimate Effects of Extreme Drought on Photosynthesis?

NASA Astrophysics Data System (ADS)

Vicca, S.; Balzarolo, M.; Filella, I.; Granier, A.; Herbst, M.; Knohl, A.; Longdoz, B.; Mund, M.; Nagy, Z.; Pintér, K.; Rambal, S.; Verbesselt, J.; Verger, A.; Zeileis, A.; Zhang, C.; Penuelas, J.

2017-12-01

Severe droughts can strongly impact photosynthesis (GPP), but the tool best suited for large-scale and long-term monitoring, satellite imagery, has yet to prove its ability to detect drought effects on GPP. Especially changes in vegetation functioning when vegetation state remains unaltered (no browning or defoliation) pose a challenge to satellite-derived indicators. We evaluated the performance of different satellite indicators to detect effect of a strong drought (that started during the European heatwave of 2003) on GPP in a beech forest in France (Hesse). While vegetation state remained largely unaffected by the drought, Eddy Covariance data revealed a substantial decrease in GPP and GPP recovered only after about three years. This three-year reduction in GPP was, however not detected by severaly commonly used reflectance indices (like NDVI and FAPAR) or by MODIS GPP product. Only he Enhanced Vegetation Index (EVI) and the Photochemical Reflectance Index (PRI) detected the drought effect, but the PRI only after normalization for absorbed light. These results were compared to a two other forests where a severe drought event had affected GPP and these data confirmed that especially the PRI normalized for absorbed light provides useful information about vegetation functioning that is not captured by other remote sensing indicators under test.

Contribution of anthropogenic warming to California drought during 2012-2015

NASA Astrophysics Data System (ADS)

Williams, P.; Seager, R.; Abatzoglou, J. T.; Cook, B.; Smerdon, J. E.; Cook, E. R.

2015-12-01

California is currently in its fourth year of a drought that has caused record-breaking rates of ground-water extraction, fallowed agricultural fields, changes to water-use policy, dangrously low lake levels, and ecological disturbances such as large wildfires and bark-beetle outbreaks. A common and important question is: to what degree can the severity of this drought in California, or of any drought globally, be blamed on human-caused global warming? Here we present the most comprehensive accounting of the natural and anthropogenic contributions to drought variability to date, and we provide an in-depth evaluation of the recent extreme drought in California. A suite of climate datasets and multiple representations of atmospheric moisture demand are used to calculate many estimates of the self-calibrated Palmer Drought Severity Index, a proxy for near-surface soil moisture, across California from 1901-2014 at high spatial resolution. Based on the ensemble of calculations, California drought conditions were record-breaking in 2014, but probably not record-breaking in 2012-2014, contrary to prior findings. Regionally, the 2012-2014 drought was record-breaking in the agriculturally important southern Central Valley and highly populated coastal areas. Contributions of individual climate variables to recent drought are also examined, including the temperature component associated with anthropogenic warming. Precipitation is the primary driver of drought variability but anthropogenic warming is estimated to have accounted for 8-27% of the observed drought anomaly in 2012-2014 and 5-18% in 2014. Analyses will be updated through 2015 for this presentation. Although natural climate variability has often masked the background effects of warming on drought, the background effect is becoming increasingly detectable and important, particularly by increased the overall likelihood of extreme California droughts. The dramatic effects of the current drought in California, combined with knowledge that the background warming-driven drought trend will continue to intensify amidst a high degree of natural climate variability, highlight the critical need for a long-term outlook on drought resilience even though wet conditions are likely to soon mitigate the current drought event.

A drought severity climatology for the Carpathian Region using Sc-PDSI

NASA Astrophysics Data System (ADS)

Antofie, Tiberiu; Naumann, Gustavo; Spinoni, Jonathan; Weynants, Melanie; Szalai, Sandor; Szentimrey, Tamas; Bihari, Zita; Vogt, Jürgen

2013-04-01

Monthly grids of the self-calibrating Palmer Drought Severity Index (Sc-PDSI) have been calculated for the period 1961-2010 for the Carpathian Region (17˚-27˚E, 44˚-50˚N) with a spatial resolution of 0.1˚x 0.1˚. Using the Sc-PDSI and the assumptions of the Palmer Drought Model (PDM), the approximated precipitation required for drought termination (achieved when the Sc-PDSI turns back above -0.5) and amelioration (achieved when the Sc-PDSI value turns back above -2.0) are computed for periods of 1, 3, 6, and 9 months. The Sc-PDSI is based on a modified version of the Palmer Drought Severity Index (PDSI), first introduced by Palmer (1965) with the intent to measure the cumulative departure (related to local normal conditions) of moisture supply and demand. Due to its empirically derived climatic characteristic (K) and duration factors - limited to U.S. climatic conditions - Wells et al. (2004) improved it and transformed the PDSI into the Sc-PDSI, which is more appropriate for spatial comparisons in different climatic regions. The Sc-PDSI is based on the supply-and-demand concept of a complex water budget system based on precipitation and temperature records and also on the soil characteristics at any location. The inputs used in this study are the Available Water Capacity of the soil (AWC) derived from the soil texture (European Soil Database of JRC) with a spatial resolution of 0.1˚x0.1˚, Potential Evapo-Transpiration (PET), and 6 hydrological parameters of the soil water balance: recharge, runoff, loss, and their potential values (used in the calculation of Palmer's constants to define the normal climate for the specific location, i.e. the so called CAFEC). PET has been computed using the 0.1˚x 0.1˚ gridded monthly precipitation and mean temperature for 1961-2010 provided by the CARPATCLIM project in the framework of the construction of a Climate Atlas for the Carpathian Region. The Sc-PDSI focuses on the monthly anomalies of the soil moisture, thus it was chosen to describe the spatio-temporal variability of the soil moisture availability across the Carpathian Region. This study provides an overview of drought events in the Carpathian Region over the last 50 years; moreover, a comparison amongst the results obtained on the same region and period of interest by means of the Sc-PDSI, SPI and SPEI is shown. Eventually, we discuss the possibility to reduce the uncertainty in the determination of the beginning and ending of drought conditions and we provide a quantitative measure of the probability that a drought event will be ameliorated or terminated in the next month.

Effects of climate change adaptation scenarios on perceived spatio-temporal characteristics of drought events

NASA Astrophysics Data System (ADS)

Vidal, J.-P.; Martin, E.; Kitova, N.; Najac, J.; Soubeyroux, J.-M.

2012-04-01

Drought events develop in both space and time and they are therefore best described through summary joint spatio-temporal characteristics, like mean duration, mean affected area and total magnitude. This study addresses the issue of future projections of such characteristics of drought events over France through three main research questions: (1) Are downscaled climate projections able to reproduce spatio-temporal characteristics of meteorological and agricultural droughts in France over a present-day period? (2) How such characteristics will evolve over the 21st century under different emissions scenarios? (3) How would perceived drought characteristics evolve under theoretical adaptation scenarios? These questions are addressed using the Isba land surface model, downscaled climate projections from the ARPEGE General Circulation Model under three emissions scenarios, as well as results from a previously performed 50-year multilevel and multiscale drought reanalysis over France (Vidal et al., 2010). Spatio-temporal characteristics of meteorological and agricultural drought events are computed using the Standardized Precipitation Index (SPI) and the Standardized Soil Wetness Index (SSWI), respectively, and for time scales of 3 and 12 months. Results first show that the distributions of joint spatio-temporal characteristics of observed events are well reproduced by the downscaled hydroclimate projections over a present-day period. All spatio-temporal characteristics of drought events are then found to dramatically increase over the 21st century under all considered emissions scenarios, with stronger changes for agricultural droughts. Two theoretical adaptation scenarios are eventually built based on hypotheses of adaptation to evolving climate and hydrological normals. The two scenarios differ by the way the transient adaptation is performed for a given date in the future, with reference to the normals over either the previous 30-year window ("retrospective" adaptation) or over a 30-year period centred around the date considered ("prospective" adaptation). These adaptation scenarios are translated into local-scale transient drought thresholds, as opposed to a non-adaptation scenario where the drought threshold remains constant. The perceived spatio-temporal characteristics derived from the theoretical adaptation scenarios show much reduced changes, but they call for more realistic scenarios at both the catchment and national scale in order to accurately assess the combined effect of local-scale adaptation and global-scale mitigation. This study thus proposes a proof of concept for using standardized drought indices for (1) assessing projections of spatio-temporal drought characteristics and (2) building theoretical adaptation scenarios and associated perceived changes in hydrological impact studies (Vidal et al., submitted). Vidal J.-P., Martin E., Franchistéguy L., Habets F., Soubeyroux J.-M., Blanchard M. & Baillon M. (2010) Multilevel and multiscale drought reanalysis over France with the Safran-Isba-Modcou hydrometeorological suite. Hydrology and Earth System Sciences, 14, 459-478.doi: 10.5194/hess-14-459-2010 Vidal J.-P., Martin E., Kitova N., Najac J. & Soubeyroux, J. M. (submitted) Evolution of spatio-temporal drought characteristics: validation, projections and effect of adaptation scenarios. Submitted to Hydrology and earth System Sciences

On the coupling between precipitation and potential evapotranspiration: contributions to decadal drought anomalies in the Southwest China

Treesearch

Shanlei Sun; Haishan Chen; Weimin Ju; Guojie Wang; Ge Sun; Jin Huang; Hedi Ma; Chujie Gao; Wenjian Hua; Guixia Yan

2016-01-01

Under the exacerbation of climate change, cli· mate extreme events. especially for drought, happened frequently and intensively across the globe with greater spatial differences. We used the Standardized Precipitation-Evapotranspiration Index computed from the routine meteorological observations at 269 sites in Southwest China (SWC) to study the drought characteristics...

On the visualization of water-related big data: extracting insights from drought proxies' datasets

NASA Astrophysics Data System (ADS)

Diaz, Vitali; Corzo, Gerald; van Lanen, Henny A. J.; Solomatine, Dimitri

2017-04-01

Big data is a growing area of science where hydroinformatics can benefit largely. There have been a number of important developments in the area of data science aimed at analysis of large datasets. Such datasets related to water include measurements, simulations, reanalysis, scenario analyses and proxies. By convention, information contained in these databases is referred to a specific time and a space (i.e., longitude/latitude). This work is motivated by the need to extract insights from large water-related datasets, i.e., transforming large amounts of data into useful information that helps to better understand of water-related phenomena, particularly about drought. In this context, data visualization, part of data science, involves techniques to create and to communicate data by encoding it as visual graphical objects. They may help to better understand data and detect trends. Base on existing methods of data analysis and visualization, this work aims to develop tools for visualizing water-related large datasets. These tools were developed taking advantage of existing libraries for data visualization into a group of graphs which include both polar area diagrams (PADs) and radar charts (RDs). In both graphs, time steps are represented by the polar angles and the percentages of area in drought by the radios. For illustration, three large datasets of drought proxies are chosen to identify trends, prone areas and spatio-temporal variability of drought in a set of case studies. The datasets are (1) SPI-TS2p1 (1901-2002, 11.7 GB), (2) SPI-PRECL0p5 (1948-2016, 7.91 GB) and (3) SPEI-baseV2.3 (1901-2013, 15.3 GB). All of them are on a monthly basis and with a spatial resolution of 0.5 degrees. First two were retrieved from the repository of the International Research Institute for Climate and Society (IRI). They are included into the Analyses Standardized Precipitation Index (SPI) project (iridl.ldeo.columbia.edu/SOURCES/.IRI/.Analyses/.SPI/). The third dataset was recovered from the Standardized Precipitation Evaporation Index (SPEI) Monitor (digital.csic.es/handle/10261/128892). PADs were found suitable to identify the spatio-temporal variability and prone areas of drought. Drought trends were visually detected by using both PADs and RDs. A similar approach can be followed to include other types of graphs to deal with the analysis of water-related big data. Key words: Big data, data visualization, drought, SPI, SPEI

Variability and trends in global drought

USGS Publications Warehouse

McCabe, Gregory J.; Wolock, David M.

2015-01-01

Monthly precipitation (P) and potential evapotranspiration (PET) from the CRUTS3.1 data set are used to compute monthly P minus PET (PMPE) for the land areas of the globe. The percent of the global land area with annual sums of PMPE less than zero are used as an index of global drought (%drought) for 1901 through 2009. Results indicate that for the past century %drought has not changed, even though global PET and temperature (T) have increased. Although annual global PET and T have increased, annual global P also has increased and has mitigated the effects of increased PET on %drought.

Combining multiple sources of data to inform conservation of Lesser Prairie-Chicken populations

USGS Publications Warehouse

Ross, Beth; Haukos, David A.; Hagen, Christian A.; Pitman, James

2018-01-01

Conservation of small populations is often based on limited data from spatially and temporally restricted studies, resulting in management actions based on an incomplete assessment of the population drivers. If fluctuations in abundance are related to changes in weather, proper management is especially important, because extreme weather events could disproportionately affect population abundance. Conservation assessments, especially for vulnerable populations, are aided by a knowledge of how extreme events influence population status and trends. Although important for conservation efforts, data may be limited for small or vulnerable populations. Integrated population models maximize information from various sources of data to yield population estimates that fully incorporate uncertainty from multiple data sources while allowing for the explicit incorporation of environmental covariates of interest. Our goal was to assess the relative influence of population drivers for the Lesser Prairie-Chicken (Tympanuchus pallidicinctus) in the core of its range, western and southern Kansas, USA. We used data from roadside lek count surveys, nest monitoring surveys, and survival data from telemetry monitoring combined with climate (Palmer drought severity index) data in an integrated population model. Our results indicate that variability in population growth rate was most influenced by variability in juvenile survival. The Palmer drought severity index had no measurable direct effects on adult survival or mean number of offspring per female; however, there were declines in population growth rate following severe drought. Because declines in population growth rate occurred at a broad spatial scale, declines in response to drought were likely due to decreases in chick and juvenile survival rather than emigration outside of the study area. Overall, our model highlights the importance of accounting for environmental and demographic sources of variability, and provides a thorough method for simultaneously evaluating population demography in response to long-term climate effects.

Relationship of the South Asian Monsoon and Regional Drought with Distinct Equatorial Pacific SST Patterns on Interannual and Decadal Timescales

NASA Astrophysics Data System (ADS)

Hernandez, M.; Ummenhofer, C.; Anchukaitis, K. J.

2014-12-01

The Asian monsoon system influences the lives of over 60% of the planet's population, with widespread socioeconomic effects resulting from weakening or failure of monsoon rains. Spatially broad and temporally extended drought episodes have been known to dramatically influence human history, including the Strange Parallels Drought in the mid-18th century. Here, we explore the dynamics of sustained monsoon failure using the Monsoon Asia Drought Atlas - a high-resolution network of hydro-climatically sensitive tree-ring records - and a 1300-year pre-industrial control run of the Community Earth System Model (CESM). Spatial drought patterns in the instrumental and model-based Palmer Drought Severity Index (PDSI) during years with extremely weakened South Asian monsoon are similar to those reconstructed during the Strange Parallels Drought in the MADA. We further explore how the large-scale Indo-Pacific climate during weakened South Asian monsoon differs between interannual and decadal timescales. The Strange Parallels Drought pattern is observed during March-April-May primarily over Southeast Asia, with decreased precipitation and reduced moisture fluxes, while anomalies in June-July-August are confined to the Indian subcontinent during both individual and decadal events. Individual years with anomalous drying exhibit canonical El Niño conditions over the eastern equatorial Pacific and associated shifts in the Walker circulation, while decadal events appear to be related to anomalous warming around the dateline in the equatorial Pacific, typical of El Niño Modoki events. The results suggest different dynamical processes influence drought at different time scales through distinct remote ocean influences.

Spatial hydrological drought characteristics in Karkheh River basin, southwest Iran using copulas

NASA Astrophysics Data System (ADS)

Dodangeh, Esmaeel; Shahedi, Kaka; Shiau, Jenq-Tzong; MirAkbari, Maryam

2017-08-01

Investigation on drought characteristics such as severity, duration, and frequency is crucial for water resources planning and management in a river basin. While the methodology for multivariate drought frequency analysis is well established by applying the copulas, the estimation on the associated parameters by various parameter estimation methods and the effects on the obtained results have not yet been investigated. This research aims at conducting a comparative analysis between the maximum likelihood parametric and non-parametric method of the Kendall τ estimation method for copulas parameter estimation. The methods were employed to study joint severity-duration probability and recurrence intervals in Karkheh River basin (southwest Iran) which is facing severe water-deficit problems. Daily streamflow data at three hydrological gauging stations (Tang Sazbon, Huleilan and Polchehr) near the Karkheh dam were used to draw flow duration curves (FDC) of these three stations. The Q_{75} index extracted from the FDC were set as threshold level to abstract drought characteristics such as drought duration and severity on the basis of the run theory. Drought duration and severity were separately modeled using the univariate probabilistic distributions and gamma-GEV, LN2-exponential, and LN2-gamma were selected as the best paired drought severity-duration inputs for copulas according to the Akaike Information Criteria (AIC), Kolmogorov-Smirnov and chi-square tests. Archimedean Clayton, Frank, and extreme value Gumbel copulas were employed to construct joint cumulative distribution functions (JCDF) of droughts for each station. Frank copula at Tang Sazbon and Gumbel at Huleilan and Polchehr stations were identified as the best copulas based on the performance evaluation criteria including AIC, BIC, log-likelihood and root mean square error (RMSE) values. Based on the RMSE values, nonparametric Kendall-τ is preferred to the parametric maximum likelihood estimation method. The results showed greater drought return periods by the parametric ML method in comparison to the nonparametric Kendall τ estimation method. The results also showed that stations located in tributaries (Huleilan and Polchehr) have close return periods, while the station along the main river (Tang Sazbon) has the smaller return periods for the drought events with identical drought duration and severity.

WRF added value to capture the spatio-temporal drought variability

NASA Astrophysics Data System (ADS)

García-Valdecasas Ojeda, Matilde; Quishpe-Vásquez, César; Raquel Gámiz-Fortis, Sonia; Castro-Díez, Yolanda; Jesús Esteban-Parra, María

2017-04-01

Regional Climate Models (RCM) has been widely used as a tool to perform high resolution climate fields in areas with high climate variability such as Spain. However, the outputs provided by downscaling techniques have many sources of uncertainty associated at different aspects. In this study, the ability of the Weather Research and Forecasting (WRF) model to capture drought conditions has been analyzed. The WRF simulation was carried out for a period that spanned from 1980 to 2010 over a domain centered in the Iberian Peninsula with a spatial resolution of 0.088°, and nested in the coarser EURO-CORDEX domain (0.44° spatial resolution). To investigate the spatiotemporal drought variability, the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI) has been computed at two different timescales: 3- and 12-months due to its suitability to study agricultural and hydrological droughts. The drought indices computed from WRF outputs were compared with those obtained from the observational (MOTEDAS and MOPREDAS) datasets. In order to assess the added value provided by downscaled fields, these indices were also computed from the ERA-Interim Re-Analysis database, which provides the lateral and boundary conditions of the WRF simulations. Results from this study indicate that WRF provides a noticeable benefit with respect to ERA-Interim for many regions in Spain in terms of drought indices, greater for SPI than for SPEI. The improvement offered by WRF depends on the region, index and timescale analyzed, being greater at longer timescales. These findings prove the reliability of the downscaled fields to detect drought events and, therefore, it is a remarkable source of knowledge for a suitable decision making related to water-resource management. Keywords: Drought, added value, Regional Climate Models, WRF, SPEI, SPI. Acknowledgements: This work has been financed by the projects P11-RNM-7941 (Junta de Andalucía-Spain) and CGL2013-48539-R (MINECO-Spain, FEDER).

Utilizing Objective Drought Thresholds to Improve Drought Monitoring with the SPI

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Inter-comparison of weather and circulation type classifications for hydrological drought development

NASA Astrophysics Data System (ADS)

Fleig, Anne K.; Tallaksen, Lena M.; Hisdal, Hege; Stahl, Kerstin; Hannah, David M.

Classifications of weather and circulation patterns are often applied in research seeking to relate atmospheric state to surface environmental phenomena. However, numerous procedures have been applied to define the patterns, thus limiting comparability between studies. The COST733 Action “ Harmonisation and Applications of Weather Type Classifications for European regions” tests 73 different weather type classifications (WTC) and their associate weather types (WTs) and compares the WTCs’ utility for various applications. The objective of this study is to evaluate the potential of these WTCs for analysis of regional hydrological drought development in north-western Europe. Hydrological drought is defined in terms of a Regional Drought Area Index (RDAI), which is based on deficits derived from daily river flow series. RDAI series (1964-2001) were calculated for four homogeneous regions in Great Britain and two in Denmark. For each region, WTs associated with hydrological drought development were identified based on antecedent and concurrent WT-frequencies for major drought events. The utility of the different WTCs for the study of hydrological drought development was evaluated, and the influence of WTC attributes, i.e. input variables, number of defined WTs and general classification concept, on WTC performance was assessed. The objective Grosswetterlagen (OGWL), the objective Second-Generation Lamb Weather Type Classification (LWT2) with 18 WTs and two implementations of the objective Wetterlagenklassifikation (WLK; with 40 and 28 WTs) outperformed all other WTCs. In general, WTCs with more WTs (⩾27) were found to perform better than WTCs with less (⩽18) WTs. The influence of input variables was not consistent across the different classification procedures, and the performance of a WTC was determined primarily by the classification procedure itself. Overall, classification procedures following the relatively simple general classification concept of predefining WTs based on thresholds, performed better than those based on more sophisticated classification concepts such as deriving WTs by cluster analysis or artificial neural networks. In particular, PCA based WTCs with 9 WTs and automated WTCs with a high number of predefined WTs (subjectively and threshold based) performed well. It is suggested that the explicit consideration of the air flow characteristics of meridionality, zonality and cyclonicity in the definition of WTs is a useful feature for a WTC when analysing regional hydrological drought development.

Rice yield in response to climate trends and drought index in the Mun River Basin, Thailand.

PubMed

Prabnakorn, Saowanit; Maskey, Shreedhar; Suryadi, F X; de Fraiture, Charlotte

2018-04-15

Rice yields in Thailand are among the lowest in Asia. In northeast Thailand where about 90% of rice cultivation is rain-fed, climate variability and change affect rice yields. Understanding climate characteristics and their impacts on the rice yield is important for establishing proper adaptation and mitigation measures to enhance productivity. In this paper, we investigate climatic conditions of the past 30years (1984-2013) and assess the impacts of the recent climate trends on rice yields in the Mun River Basin in northeast Thailand. We also analyze the relationship between rice yield and a drought indicator (Standardized Precipitation and Evapotranspiration Index, SPEI), and the impact of SPEI trends on the yield. Our results indicate that the total yield losses due to past climate trends are rather low, in the range of <50kg/ha per decade (3% of actual average yields). In general, increasing trends in minimum and maximum temperatures lead to modest yield losses. In contrast, precipitation and SPEI-1, i.e. SPEI based on one monthly data, show positive correlations with yields in all months, except in the wettest month (September). If increasing trends of temperatures during the growing season persist, a likely climate change scenario, there is high possibility that the yield losses will become more serious in future. In this paper, we show that the drought index SPEI-1 detects soil moisture deficiency and crop stress in rice better than precipitation or precipitation based indicators. Further, our results emphasize the importance of spatial and temporal resolutions in detecting climate trends and impacts on yields. Copyright © 2017 Elsevier B.V. All rights reserved.

Analysis of the spatial-temporal variation characteristics of vegetative drought and its relationship with meteorological factors in China from 1982 to 2010.

PubMed

Shen, Qiu; Liang, Liang; Luo, Xiang; Li, Yanjun; Zhang, Lianpeng

2017-08-25

Drought is a complex natural phenomenon that can cause reduced water supplies and can consequently have substantial effects on agriculture and socioeconomic activities. The objective of this study was to gain a better understanding of the spatial-temporal variation characteristics of vegetative drought and its relationship with meteorological factors in China. The Vegetation Condition Index (VCI) dataset calculated from NOAA/AVHRR images from 1982 to 2010 was used to analyse the spatial-temporal variation characteristics of vegetative drought in China. This study also examined the trends in meteorological factors and their influences on drought using monitoring data collected from 686 national ground meteorological stations. The results showed that the VCI appeared to slowly rise in China from 1982 to 2010. From 1982 to 1999, the VCI rose slowly. Then, around 2000, the VCI exhibited a severe fluctuation before it entered into a relatively stable stage. Drought frequencies in China were higher, showing a spatial distribution feature of "higher in the north and lower in the south". Based on the different levels of drought, the frequencies of mild and moderate drought in four geographical areas were higher, and the frequency of severe drought was higher only in ecologically vulnerable areas, such as the Tarim Basin and the Qaidam Basin. Drought was mainly influenced by meteorological factors, which differed regionally. In the northern region, the main influential factor was sunshine duration, while the other factors showed minimal effects. In the southern region and Tibetan Plateau, the main influential factors were sunshine duration and temperature. In the northwestern region, the main influential factors were wind velocity and station atmospheric pressure.

Water and Forest Health: Drought Stress as a Core Driver of Forest Disturbances and Tree Mortality in Western North America

NASA Astrophysics Data System (ADS)

Allen, C. D.; Williams, P.

2012-12-01

Increasing warmth and dry climate conditions have affected large portions of western North America in recent years, causing elevated levels of both chronic and acute forest drought stress. In turn, increases in drought stress amplify the incidence and severity of the most significant forest disturbances in this region, including wildfire, drought-induced tree mortality, and outbreaks of damaging insects and diseases. Regional patterns of drought stress and various forest disturbances are reviewed, including interactions among climate and the various disturbance processes; similar global-scale patterns and trends of drought-amplified forest die-off and high-severity wildfire also are addressed. New research is presented that derives a tree-ring-based Forest Drought Stress Index (FDSI) for the three most widespread conifer species (Pinus edulis, Pinus ponderosa, and Pseudotsuga menziesii) in the southwestern US (Arizona, New Mexico), demonstrating nonlinear escalation of FDSI to levels unprecedented in the past 1000 years, in response to both drought and especially recent warming. This new work further highlights strong correlations between drought stress and amplified forest disturbances (fire, bark beetle outbreaks), and projects that by ca. 2050 anticipated regional warming will cause mean FDSI levels to reach extreme levels that may exceed thresholds for the survival of current tree species in large portions of their current range. Given recent trends of forest disturbance and projections for substantially warmer temperatures and greater drought stress for much of western North America in coming years, the growing risks to western forest health are becoming clear. This emerging understanding suggests an urgent need to determine potentials and methods for managing water on-site to maintain the vigor and resilience of western forests in the face of increasing levels of climate-induced water stress.

How well do CMIP5 climate simulations replicate historical trends and patterns of droughts?

DOE PAGES

Nasrollahi, Nasrin; AghaKouchak, Amir; Cheng, Linyin; ...

2015-04-26

Assessing the uncertainties and understanding the deficiencies of climate models are fundamental to developing adaptation strategies. The objective of this study is to understand how well Coupled Model Intercomparison-Phase 5 (CMIP5) climate model simulations replicate ground-based observations of continental drought areas and their trends. The CMIP5 multimodel ensemble encompasses the Climatic Research Unit (CRU) ground-based observations of area under drought at all time steps. However, most model members overestimate the areas under extreme drought, particularly in the Southern Hemisphere (SH). Furthermore, the results show that the time series of observations and CMIP5 simulations of areas under drought exhibit more variabilitymore » in the SH than in the Northern Hemisphere (NH). The trend analysis of areas under drought reveals that the observational data exhibit a significant positive trend at the significance level of 0.05 over all land areas. The observed trend is reproduced by about three-fourths of the CMIP5 models when considering total land areas in drought. While models are generally consistent with observations at a global (or hemispheric) scale, most models do not agree with observed regional drying and wetting trends. Over many regions, at most 40% of the CMIP5 models are in agreement with the trends of CRU observations. The drying/wetting trends calculated using the 3 months Standardized Precipitation Index (SPI) values show better agreement with the corresponding CRU values than with the observed annual mean precipitation rates. As a result, pixel-scale evaluation of CMIP5 models indicates that no single model demonstrates an overall superior performance relative to the other models.« less