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 Hybrid Index for Characterizing Drought Based on a Nonparametric Kernel Estimator

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

Huang, Shengzhi; Huang, Qiang; Leng, Guoyong

This study develops a nonparametric multivariate drought index, namely, the Nonparametric Multivariate Standardized Drought Index (NMSDI), by considering the variations of both precipitation and streamflow. Building upon previous efforts in constructing Nonparametric Multivariate Drought Index, we use the nonparametric kernel estimator to derive the joint distribution of precipitation and streamflow, thus providing additional insights in drought index development. The proposed NMSDI are applied in the Wei River Basin (WRB), based on which the drought evolution characteristics are investigated. Results indicate: (1) generally, NMSDI captures the drought onset similar to Standardized Precipitation Index (SPI) and drought termination and persistence similar tomore » Standardized Streamflow Index (SSFI). The drought events identified by NMSDI match well with historical drought records in the WRB. The performances are also consistent with that by an existing Multivariate Standardized Drought Index (MSDI) at various timescales, confirming the validity of the newly constructed NMSDI in drought detections (2) An increasing risk of drought has been detected for the past decades, and will be persistent to a certain extent in future in most areas of the WRB; (3) the identified change points of annual NMSDI are mainly concentrated in the early 1970s and middle 1990s, coincident with extensive water use and soil reservation practices. This study highlights the nonparametric multivariable drought index, which can be used for drought detections and predictions efficiently and comprehensively.« less

Drought assessment in the Dongliao River basin: traditional approaches vs. generalized drought assessment index based on water resources systems

NASA Astrophysics Data System (ADS)

Weng, B. S.; Yan, D. H.; Wang, H.; Liu, J. H.; Yang, Z. Y.; Qin, T. L.; Yin, J.

2015-08-01

Drought is firstly a resource issue, and with its development it evolves into a disaster issue. Drought events usually occur in a determinate but a random manner. Drought has become one of the major factors to affect sustainable socioeconomic development. In this paper, we propose the generalized drought assessment index (GDAI) based on water resources systems for assessing drought events. The GDAI considers water supply and water demand using a distributed hydrological model. We demonstrate the use of the proposed index in the Dongliao River basin in northeastern China. The results simulated by the GDAI are compared to observed drought disaster records in the Dongliao River basin. In addition, the temporal distribution of drought events and the spatial distribution of drought frequency from the GDAI are compared with the traditional approaches in general (i.e., standard precipitation index, Palmer drought severity index and rate of water deficit index). Then, generalized drought times, generalized drought duration, and generalized drought severity were calculated by theory of runs. Application of said runs at various drought levels (i.e., mild drought, moderate drought, severe drought, and extreme drought) during the period 1960-2010 shows that the centers of gravity of them all distribute in the middle reaches of Dongliao River basin, and change with time. The proposed methodology may help water managers in water-stressed regions to quantify the impact of drought, and consequently, to make decisions for coping with drought.

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.

Relationship between Climate Variability, Wildfire Risk, and Wildfire Occurrence in Wildland-Urban Interface of the Southwestern United States

NASA Astrophysics Data System (ADS)

Kafatos, M.; Kim, S. H.; Jia, S.; Nghiem, S. V.

2017-12-01

As housing units in or near wildlands have grown, the wildland-urban interface (WUI) contain at present approximately one-third of all housing in the contiguous US. Wildfires are a part of the natural cycle in the Southwestern United States (SWUS) but the increasing trend of WUI has made wildfires a serious high-risk hazard. The expansion of WUI has elevated wildfire risks by increasing the chance of human caused ignitions and past fire suppression in the area. Previous studies on climate variability have shown that the SWUS region is prone to frequent droughts and has suffered from severe wildfires in the recent decade. Therefore, assessing the increased vulnerability to the wildfire in WUI is crucial for proactive adaptation under climate change. Our previous study has shown that a strong correlation between North Atlantic Oscillation (NAO) and temperature was found during March-June in the SWUS. The abnormally warm and dry spring conditions, combined with suppression of winter precipitation, can cause an early start of a fire season and high fire risk throughout the summer and fall. Therefore, it is crucial to investigate the connections between climate variability and wildfire danger characteristics. This study aims to identify climate variability using multiple climate indices such as NAO, El Niño-Southern Oscillation and the Pacific Decadal Oscillation closely related with droughts in the SWUS region. Correlation between the variability and fire frequency and severity in WUI were examined. Also, we investigated climate variability and its relationship on local wildfire potential using both Keetch-Byram Drought Index (KBDI) and Fire Weather Index (FWI) which have been used to assessing wildfire potential in the U.S.A and Canada, respectively. We examined the long-term variability of the fire potential indices and relationships between the indices and historical occurrence in WUI using multi-decadal reanalysis data sets. Following our analysis, we investigated

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.

Drought characterisation based on an agriculture-oriented standardised precipitation index

NASA Astrophysics Data System (ADS)

Tigkas, Dimitris; Vangelis, Harris; Tsakiris, George

2018-03-01

Drought is a major natural hazard with significant effects in the agricultural sector, especially in arid and semi-arid regions. The accurate and timely characterisation of agricultural drought is crucial for devising contingency plans, including the necessary mitigation measures. Many drought indices have been developed during the last decades for drought characterisation and analysis. One of the most widely used indices worldwide is the Standardised Precipitation Index (SPI). Although other comprehensive indices have been introduced over the years, SPI remains the most broadly accepted index due to a number of reasons, the most important of which are its simple structure and the fact that it uses only precipitation data. In this paper, a modified version of SPI is proposed, namely the Agricultural Standardised Precipitation Index (aSPI), based on the substitution of the total precipitation by the effective precipitation, which describes more accurately the amount of water that can be used productively by the plants. Further, the selection of the most suitable reference periods and time steps for agricultural drought identification using aSPI is discussed. This conceptual enhancement of SPI aims at improving the suitability of the index for agricultural drought characterisation, while retaining the advantages of the original index, including its dependence only on precipitation data. The evaluation of the performance of both SPI and aSPI in terms of correlating drought magnitude with crop yield response in four regions of Greece under Mediterranean conditions indicated that aSPI is more robust than the original index in identifying agricultural drought.

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.

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.

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.

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.

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

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

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

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

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

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

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

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

Copula-based drought risk assessment combined with an integrated index in the Wei River Basin, China

NASA Astrophysics Data System (ADS)

Chang, Jianxia; Li, Yunyun; Wang, Yimin; Yuan, Meng

2016-09-01

It is critical to assess drought risk based on a reliably integrated drought index incorporating comprehensive information of meteorology, hydrology and agriculture drought indices, which is of great value for further understanding the future drought tendency, prevention and mitigation. Thus, the primary objective of this study was to focus on constructing a multivariate integrated drought index (MIDI) by coupling four drought indices (i.e., Precipitation Anomaly Percentage (PAP), Runoff Anomaly Percentage (RAP), Standardized Precipitation Index with 6-month aggregation time step (SPI6) and Modified Palmer Drought Severity Index (MPDSI)) to objectively and comprehensively investigate drought risk. The variable fuzzy set theory and entropy weight method are used during the MIDI construction process. Based on the MIDI, a drought event including drought duration and severity is redefined using run theory. Then copula-based drought risk is fully assessed through the joint probability distribution of drought duration and severity. Results indicate the following: (1) the constructed MIDI is consistent with the Standardized Precipitation Index (SPI) and Runoff Anomaly Percentage (RAP) series, and it is more sensitive and effective to capture historical drought events; (2) the drought characteristics present noticeable spatial variability among five subzones, and the entire basin has 49 droughts with the longest drought duration spanning 8.55 months; and (3) the mainstream, especially the middle and lower reaches, has higher occurrences of severe droughts for approximately every 10 years.

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.

Wildfire Risk Mapping over the State of Mississippi: Land Surface Modeling Approach

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

Cooke, William H.; Mostovoy, Georgy; Anantharaj, Valentine G

2012-01-01

Three fire risk indexes based on soil moisture estimates were applied to simulate wildfire probability over the southern part of Mississippi using the logistic regression approach. The fire indexes were retrieved from: (1) accumulated difference between daily precipitation and potential evapotranspiration (P-E); (2) top 10 cm soil moisture content simulated by the Mosaic land surface model; and (3) the Keetch-Byram drought index (KBDI). The P-E, KBDI, and soil moisture based indexes were estimated from gridded atmospheric and Mosaic-simulated soil moisture data available from the North American Land Data Assimilation System (NLDAS-2). Normalized deviations of these indexes from the 31-year meanmore » (1980-2010) were fitted into the logistic regression model describing probability of wildfires occurrence as a function of the fire index. It was assumed that such normalization provides more robust and adequate description of temporal dynamics of soil moisture anomalies than the original (not normalized) set of indexes. The logistic model parameters were evaluated for 0.25 x0.25 latitude/longitude cells and for probability representing at least one fire event occurred during 5 consecutive days. A 23-year (1986-2008) forest fires record was used. Two periods were selected and examined (January mid June and mid September December). The application of the logistic model provides an overall good agreement between empirical/observed and model-fitted fire probabilities over the study area during both seasons. The fire risk indexes based on the top 10 cm soil moisture and KBDI have the largest impact on the wildfire odds (increasing it by almost 2 times in response to each unit change of the corresponding fire risk index during January mid June period and by nearly 1.5 times during mid September-December) observed over 0.25 x0.25 cells located along the state of Mississippi Coast line. This result suggests a rather strong control of fire risk indexes on fire occurrence

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

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.

[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.

A general framework for multivariate multi-index drought prediction based on Multivariate Ensemble Streamflow Prediction (MESP)

NASA Astrophysics Data System (ADS)

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

2016-08-01

Drought is among the costliest natural hazards worldwide and extreme drought events in recent years have caused huge losses to various sectors. Drought prediction is therefore critically important for providing early warning information to aid decision making to cope with drought. Due to the complicated nature of drought, it has been recognized that the univariate drought indicator may not be sufficient for drought characterization and hence multivariate drought indices have been developed for drought monitoring. Alongside the substantial effort in drought monitoring with multivariate drought indices, it is of equal importance to develop a drought prediction method with multivariate drought indices to integrate drought information from various sources. This study proposes a general framework for multivariate multi-index drought prediction that is capable of integrating complementary prediction skills from multiple drought indices. The Multivariate Ensemble Streamflow Prediction (MESP) is employed to sample from historical records for obtaining statistical prediction of multiple variables, which is then used as inputs to achieve multivariate prediction. The framework is illustrated with a linearly combined drought index (LDI), which is a commonly used multivariate drought index, based on climate division data in California and New York in the United States with different seasonality of precipitation. The predictive skill of LDI (represented with persistence) is assessed by comparison with the univariate drought index and results show that the LDI prediction skill is less affected by seasonality than the meteorological drought prediction based on SPI. Prediction results from the case study show that the proposed multivariate drought prediction outperforms the persistence prediction, implying a satisfactory performance of multivariate drought prediction. The proposed method would be useful for drought prediction to integrate drought information from various sources

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

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.

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

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.

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.

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.

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

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

Development Of Index To Assess Drought Conditions Using Geospatial Data A Case Study Of Jaisalmer District, Rajasthan, India

NASA Astrophysics Data System (ADS)

Chhajer, Vaidehi; Prabhakar, Sumati; Rama Chandra Prasad, P.

2015-12-01

The Jaisalmer district of Rajasthan province of India was known to suffer with frequent drought due to poor and delayed monsoon, abnormally high summer-temperature and insufficient water resources. However flood-like situation prevails in the drought prone Jaisalmer district of Rajasthan as torrential rains are seen to affect the region in the recent years. In the present study, detailed analysis of meteorological, hydrological and satellite data of the Jaisalmer district has been carried out for the years 2006-2008. Standardized Precipitation Index (SPI), Consecutive Dry Days (CDD) and Effective Drought Index (EDI) have been used to quantify the precipitation deficit. Standardized Water-Level Index (SWI) has been developed to assess ground-water recharge-deficit. Vegetative drought indices like Vegetation Condition Index (VCI), Temperature Condition Index (TCI), Vegetation Health Index (VHI), Normalized Difference Vegetation Index (NDVI) and Modified Soil-Adjusted Vegetation Index 2 have been calculated. We also introduce two new indices Soil based Vegetation Condition Index (SVCI) and Composite Drought Index (CDI) specifically for regions like Jaisalmer where aridity in soil and affects vegetation and water-level.

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.

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...

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

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.

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.

[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.

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

NASA Astrophysics Data System (ADS)

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

2016-08-01

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

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...

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.

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

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.

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

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.

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.

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

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.

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.

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.

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 Veg

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

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

Selection of Drought Tolerant Maize Hybrids Using Path Coefficient Analysis and Selection Index.

PubMed

Dao, Abdalla; Sanou, Jacob; V S Traore, Edgar; Gracen, Vernon; Danquah, Eric Y

2017-01-01

In drought-prone environments, direct selection for yield is not adequate because of the variable environment and genotype x environment interaction. Therefore, the use of secondary traits in addition to yield has been suggested. The relative usefulness of secondary traits as indirect selection criteria for maize grain yield is determined by the magnitudes of their genetic variance, heritability and genetic correlation with the grain yield. Forty eight testcross hybrids derived from lines with different genetic background and geographical origins plus 7 checks were evaluated in both well-watered and water-stressed conditions over two years for grain yield and secondary traits to determine the most appropriate secondary traits and select drought tolerant hybrids. Study found that broad-sense heritability of grain yield and Ear Per Plant (EPP) increased under drought stress. Ear aspect (EASP) and ear height (EHT) had larger correlation coefficients and direct effect on grain yield but in opposite direction, negative and positive respectively. Traits like, EPP, Tassel Size (TS) and Plant Recovery (PR) contributed to increase yield via EASP by a large negative indirect effect. Under drought stress, EHT had positive and high direct effect and negative indirect effect via plant height on grain yield indicating that the ratio between ear and plant heights (R-EPH) was associated to grain yield. Path coefficient analysis showed that traits EPP, TS, PR, EASP, R-EPH were important secondary traits in the present experiment. These traits were used in a selection index to classify hybrids according to their performance under drought. The selection procedure included also a Relative Decrease in Yield (RDY) index. Some secondary traits reported as significant selection criteria for selection under drought stress were not finally established in the present study. This is because the relationship between grain and secondary traits can be affected by various factors including

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.

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.

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

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.

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

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.

[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 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.

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.

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

NASA Astrophysics Data System (ADS)

Pandzic, Kreso

2016-04-01

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 1862-2012 are used. The results indicate that SPI is simpler for interpretation than PDSI. On the other side, lack of temperature within SPI, make impossible use of it on climate change applications. 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. In addition, correlation coefficients of determination between annual corn crop per hectare and SPI 9- months time scale and PDSI from May to October are shown as significant.

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

USDA-ARS?s Scientific Manuscript database

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

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.

[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.

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.

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.

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.

Two-Dimensional Hydrodynamic Modeling and Analysis of the Proposed Channel Modifications and Grade Control Structure on the Blue River near Byram's Ford Industrial Park, Kansas City, Missouri

USGS Publications Warehouse

Huizinga, Richard J.

2007-01-01

The Blue River Channel Modification project being implemented by the U.S. Army Corps of Engineers (USACE) is intended to provide flood protection within the Blue River valley in the Kansas City, Mo., metropolitan area. In the latest phase of the project, concerns have arisen about preserving the Civil War historic area of Byram's Ford and the associated Big Blue Battlefield while providing flood protection for the Byram's Ford Industrial Park. In 1996, the USACE used a physical model built at the Waterways Experiment Station (WES) in Vicksburg, Miss., to examine the feasibility of a proposed grade control structure (GCS) that would be placed downstream from the historic river crossing of Byram's Ford to provide a subtle transition of flow from the natural channel to the modified channel. The U.S. Geological Survey (USGS), in cooperation with the USACE, modified an existing two-dimensional finite element surface-water model of the river between 63d Street and Blue Parkway (the 'original model'), used the modified model to simulate the existing (as of 2006) unimproved channel and the proposed channel modifications and GCS, and analyzed the results from the simulations and those from the WES physical model. Modifications were made to the original model to create a model that represents existing (2006) conditions between the north end of Swope Park immediately upstream from 63d Street and the upstream limit of channel improvement on the Blue River (the 'model of existing conditions'). The model of existing conditions was calibrated to two measured floods. The model of existing conditions also was modified to create a model that represents conditions along the same reach of the Blue River with proposed channel modifications and the proposed GCS (the 'model of proposed conditions'). The models of existing conditions and proposed conditions were used to simulate the 30-, 50-, and 100-year recurrence floods. The discharge from the calibration flood of May 15, 1990, also

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

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

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.

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.

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

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.

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.

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

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

Spatiotemporal Variability of the Meteorological Drought in Romania using the Standardized Precipitation Index

NASA Astrophysics Data System (ADS)

Cheval, Sorin; Busuioc, Aristita; Dumitrescu, Alexandru; Birsan, Marius-Victor

2013-04-01

Drought events occur over any geographical area, and may impact severely the environment and society. In terms of economic losses, droughts are one of the major natural hazards affecting Romania, so that the topic has been constantly approached. In general, the climatic projections over the 21st century display increasing temperatures and very likely declining summer precipitation (Busuioc et al., 2010), probably causing better drought conditions. This study examines the variability of the droughts in Romania, aiming to characterize the droughts intensity, durations and frequency (a), to identify spatial and temporal patterns (b), trends (c), and potential triggering factors (d). Besides, we consider comparing the performance of different instances of the Standardized Precipitation Index (SPI) (McKee et al., 1993), such as time scale and probability distribution functions (gamma and Pearson type III), for retrieving drought characteristics. Homogenous monthly precipitation amounts from 98 weather stations run by the Romanian Meteorological Administration covering the period 1961-2010 were the primary data for calculating 1, 3, 6, and 12-month time scale SPI. The Mann-Kendall statistics sustained the trend significance examination, while Empirical Orthogonal Function (EOF) analysis synthesizes the climate signal related to spatial and temporal characteristics of variability over Romania. The SPI variability over Romania is mainly influenced by the large-scale mechanisms (e.g. North Atlantic Oscillation (NAO) and Atlantic Multidecadal Oscillation (AMO)) accounting for more than 50% from the observed variance, on second place being the Carpathians accounting for the highest influence in winter (11%). Thus, the Carpathians separate Romania in two major regions in terms of drought characteristics, namely outside and inside the mountainous arch. Significant trends towards dry conditions are noted at very few stations in winter, spring and summer, while trend to

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).

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

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

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

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

Vegetation index anomaly response to varying lengths of drought across vegetation and climatic gradients in Hawaii

NASA Astrophysics Data System (ADS)

Lucas, M.; Miura, T.; Trauernicht, C.; Frazier, A. G.

2017-12-01

A drought which results in prolonged and extended deficit in naturally available water supply and creates multiple stresses across ecosystems is classified as an ecological drought. Detecting and understanding the dynamics and response of such droughts in tropical systems, specifically across various vegetation and climatic gradients is fairly undetermined, yet increasingly important for better understandings of the ecological effects of drought. To understanding the link between what lengths and intensities of known meteorological drought triggers detectable ecological vegetation responses, a landscape scale regression analysis evaluating the response (slope) and relationship strength (R-squared) of several cumulative SPI (standard precipitation index) lengths(1, 3, 6, 12, 18, 24, 36, 48, and 60 month), to various satellite derived monthly vegetation indices anomalies (NDVI, EVI, EVI2, and LSWI) was performed across a matrix of dominant vegetation covers (grassland, shrubland, and forest) and climatic moisture zones (arid, dry, mesic, and wet). The nine different SPI lags across these climactic and vegetation gradients was suggest that stronger relationships and steeper slopes were found in dryer climates (across all vegetation covers) and finer vegetation types (across all moisture zones). Overall NDVI, EVI and EVI2 showed the best utility in these dryer climatic zones across all vegetation types. Within arid and dry areas "best" fits showed increasing lengths of cumulative SPI were with increasing vegetation coarseness respectively. Overall these findings suggest that rainfall driven drought may have a stronger impact on the ecological condition of vegetation in water limited systems with finer vegetation types ecologically responding more rapidly to meteorological drought events than coarser woody vegetation systems. These results suggest that previously and newly documented trends of decreasing rainfall and increasing drought in Hawaiian drylands may have

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.

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

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

An extended multivariate framework for drought monitoring in Mexico

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

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.

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

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.

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

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.

Research on the remote sensing methods of drought monitoring in Chongqing

NASA Astrophysics Data System (ADS)

Yang, Shiqi; Tang, Yunhui; Gao, Yanghua; Xu, Yongjin

2011-12-01

There are regional and periodic droughts in Chongqing, which impacted seriously on agricultural production and people's lives. This study attempted to monitor the drought in Chongqing with complex terrain using MODIS data. First, we analyzed and compared three remote sensing methods for drought monitoring (time series of vegetation index, temperature vegetation dryness index (TVDI), and vegetation supply water index (VSWI)) for the severe drought in 2006. Then we developed a remote sensing based drought monitoring model for Chongqing by combining soil moisture data and meteorological data. The results showed that the three remote sensing based drought monitoring models performed well in detecting the occurrence of drought in Chongqing on a certain extent. However, Time Series of Vegetation Index has stronger sensitivity in time pattern but weaker in spatial pattern; although TVDI and VSWI can reflect inverse the whole process of severe drought in 2006 summer from drought occurred - increased - relieved - increased again - complete remission in spatial domain, but TVDI requires the situation of extreme drought and extreme moist both exist in study area which it is more difficult in Chongqing; VSWI is simple and practicable, which the correlation coefficient between VSWI and soil moisture data reaches significant levels. In summary, VSWI is the best model for summer drought monitoring in Chongqing.

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.

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

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.

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.

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.

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.

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 ...

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

Meteorological drought patterns and climate change for the island of Crete

NASA Astrophysics Data System (ADS)

Koutroulis, Aristeidis G.; Vrohidou, Aggeliki K.; Tsanis, Ioannis K.; Jacob, Daniela

2010-05-01

A new index, named SN-SPI (Spatially Normalized-Standardized Precipitation Index), has been developed for assessing meteorological droughts. The SN-SPI is a variant index to SPI (Standardized Precipitation Index) and is based on the probability of precipitation at different time scales, but it is spatially normalized for improved assessment of drought severity. Results of this index incorporate the spatial distribution of precipitation and produces improved drought warnings. This index is applied in the island of Crete (Greece) and the drought results are compared to the ones of SPI. A 30-year long average monthly precipitation dataset from 130 watersheds of the island is used by the above indices for drought classification in terms of its duration and intensity. Bias adjusted monthly precipitation estimates from REMO regional climate model used to quantify the influence of global warming to drought conditions over the period 2010 - 2100. Results based on both indices from 3 basins in west, central and east part of the island show that: a) the extreme drought periods are the same (5%-7% of time) but the intensities based on SN-SPI are lower, b) the area covered by extreme droughts is 25% and 80% based on the SN-SPI and SPI respectively, c) more than half of the area of Crete is experiencing drought conditions during 46% of the 1973-2004 period and 7%, 63% and 92% for 2010-2040, 2040-2070 and 2070-2100 respectively and d) extremely dry conditions will cover 5% of the island for the future 90-year period.

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

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.

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

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.

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.

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

Use of Sequent Peak Algorithm Drought Severity Index and Hydroclimatic Reconstructions from Tree-Rings to Inform Water Supply Reliability Planning

NASA Astrophysics Data System (ADS)

Bray, B. S.; Palhegyi, G.

2015-12-01

California is in the midst of a severe drought with below average runoff since WY 2012. Within this context, many water resource managers are scrutinizing water supply reliability assumptions for planning studies. Severe droughts represent a relatively rare phenomenon, occurring only a handful of times within our limited 100-year period of watershed runoff records. Furthermore, droughts may have different runoff magnitudes and durations that inherently present a challenge for direct comparisons of one drought with another. We use the sequent peak algorithm as a drought severity index (SPADSI) that accounts for both drought magnitude and duration relative to an assumed minimum release policy and fixed level-of-development (LOD) demand modeling framework. The SPADSI allows direct, quantitative evaluation of different policy options for lessening drought severity where, for example, layering a customer rationing policy onto model results reduced the SPADSI for the historical 1976-77 drought from 520 to 450 thousand acre-feet (TAF) and 1987-92 drought from 650 to 415 TAF for 2015 LOD. A strong correlation (R2 = 0.96) between Mokelumne River watershed runoff and tree-ring hydroclimate reconstructions for neighboring American and Stanislaus watersheds from Meko et al. (2014) was the basis for an extended 1100-year historical reconstruction of Mokelumne Watershed annual runoff. The reconstructed runoff timeseries is used to investigate extended historical drought durations for the Mokelumne Watershed where shorter one- to three-year droughts are most probable durations (>90%) whereas longer duration droughts lasting as long as 10 years such as occurred in 1776-85 are also possible, though much less likely. Applying the SPADSI to the reconstructed runoff timeseries showed that recent droughts e.g. 1929-34, 1976-77, and 1987-92 are all relatively severe within this millennial context, falling on the distribution tail of the extended SPADSI dataset. These findings are

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.

Improving Multi-Sensor Drought Monitoring, Prediction and Recovery Assessment Using Gravimetry Information

NASA Astrophysics Data System (ADS)

Aghakouchak, Amir; Tourian, Mohammad J.

2015-04-01

Development of reliable drought monitoring, prediction and recovery assessment tools are fundamental to water resources management. This presentation focuses on how gravimetry information can improve drought assessment. First, we provide an overview of the Global Integrated Drought Monitoring and Prediction System (GIDMaPS) which offers near real-time drought information using remote sensing observations and model simulations. Then, we present a framework for integration of satellite gravimetry information for improving drought prediction and recovery assessment. The input data include satellite-based and model-based precipitation, soil moisture estimates and equivalent water height. Previous studies show that drought assessment based on one single indicator may not be sufficient. For this reason, GIDMaPS provides drought information based on multiple drought indicators including Standardized Precipitation Index (SPI), Standardized Soil Moisture Index (SSI) and the Multivariate Standardized Drought Index (MSDI) which combines SPI and SSI probabilistically. MSDI incorporates the meteorological and agricultural drought conditions and provides composite multi-index drought information for overall characterization of droughts. GIDMaPS includes a seasonal prediction component based on a statistical persistence-based approach. The prediction component of GIDMaPS provides the empirical probability of drought for different severity levels. In this presentation we present a new component in which the drought prediction information based on SPI, SSI and MSDI are conditioned on equivalent water height obtained from the Gravity Recovery and Climate Experiment (GRACE). Using a Bayesian approach, GRACE information is used to evaluate persistence of drought. Finally, the deficit equivalent water height based on GRACE is used for assessing drought recovery. In this presentation, both monitoring and prediction components of GIDMaPS will be discussed, and the results from 2014

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).

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.

Drought trends indicated by evapotranspiration deficit over the contiguous United States during 1896-2013

NASA Astrophysics Data System (ADS)

Kim, Daeha; Rhee, Jinyoung

2016-04-01

Evapotranspiration (ET) has received a great attention in drought assessment as it is closely related to atmospheric water demand. The hypothetical potential ET (ETp) has been predominantly used, nonetheless it does not actually exist in the hydrologic cycle. In this work, we used a complementary method for ET estimation to obtain wet-environment ET (ETw) and actual ET (ETa) from routinely observed climatic data. By combining ET deficits (ETw minus ETa) and the structure of the Standardized Precipitation-Evapotranspiration Index (SPEI), we proposed a novel ET-based drought index, the Standardized Evapotranspiration Deficit Index (SEDI). We carried out historical drought identification for the contiguous United States using temperature datasets of the PRISM Climate Group. SEDI presented spatial distributions of drought areas similar to the Palmer Drought Severity Index (PDSI) and Standardized Precipitation Index (SPI) for major drought events. It indicates that SEDI can be used for validating other drought indices. Using the non-parametric Mann-Kendall test, we found a significant decreasing trend of SEDI (increasing drought risk) similar to PDSI and SPI in the western United States. This study suggests a potential of ET-based indices for drought quantification even with no involvement of precipitation data.

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.

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.

Climate conditions and drought assessment with the Palmer Drought Severity Index in Iran: evaluation of CORDEX South Asia climate projections (2070-2099)

NASA Astrophysics Data System (ADS)

Senatore, Alfonso; Hejabi, Somayeh; Mendicino, Giuseppe; Bazrafshan, Javad; Irannejad, Parviz

2018-03-01

Climate change projections were evaluated over both the whole Iran and six zones having different precipitation regimes considering the CORDEX South Asia dataset, for assessing space-time distribution of drought occurrences in the future period 2070-2099 under RCP4.5 scenario. Initially, the performances of eight available CORDEX South Asia Regional Climate Models (RCMs) were assessed for the baseline period 1970-2005 through the GPCC v.7 precipitation dataset and the CFSR temperature dataset, which were previously selected as the most reliable within a set of five global datasets compared to 41 available synoptic stations. Though the CCLM RCM driven by the MPI-ESM-LR General Circulation Model is in general the most suitable for temperature and, together with the REMO 2009 RCM also driven by MPI-ESM-LR, for precipitation, their performances do not overwhelm other models for every season and zone in which Iranian territory was divided according to a principal component analysis approach. Hence, a weighting approach was tested and adopted to take into account useful information from every RCM in each of the six zones. The models resulting more reliable compared to current climate show a strong precipitation decrease. Weighted average predicts an overall yearly precipitation decrease of about 20%. Temperature projections provide a mean annual increase of 2.4 °C. Future drought scenarios were depicted by means of the self-calibrating version of the Palmer drought severity index (SC-PDSI) model. Weighted average predicts a sharp drying that can be configured as a real shift in mean climate conditions, drastically affecting water resources of the country.

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.

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

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.

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

Spatial comparability of drought characteristics and related return periods in mainland China over 1961-2013

NASA Astrophysics Data System (ADS)

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

2017-07-01

The proper understanding of the spatiotemporal characteristics of multi-year droughts and return periods is important for drought risk assessment. This study evaluated and compared the spatiotemporal variations of drought characteristics and return periods within mainland China between 1961 and 2013. Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI) and Composite Index (CI) were calculated at multiple timescales, the run theory was used for objective identification and characterization of drought events while Kendall's τ method was used to analyze their dependencies. Within the univariate framework, marginal distributions of duration, severity, and peak were derived by fitting Exponential, Weibull and GDP distributions respectively and the drought return periods was investigated and mapped. Comparison of drought indices showed that SPEI and CI performed better than SPI in delineating spatial patterns of drought characteristics. This might be attributed to the temperature effect on evapotranspiration and therefore on drought index. Considering the increasing trend in reference evapotranspiration in the 21st century, the importance of utilizing temperature-based drought index is imperative. Severe and extreme droughts occurred in the late 1990s in many places in China while persistent multi-year severe droughts occurred more frequently over North China, Northeast China, Northwest China and Southwest China. The spatial patterns showed that regions characterized by higher drought severity were associated with higher drought duration. The North China, Northwest China, and Southwest China had much longer drought durations during the 1990s and 2000s. As droughts normally cover large areas, regional drought return periods has been showed to be more effective in providing support for drought management than station based drought return periods. Studies on the spatial comparability of drought return periods across mainland

Results of Large Area Crop Inventory Experiment (LACIE) drought analysis (South Dakota drought 1976)

NASA Technical Reports Server (NTRS)

Thompson, D. R.

1976-01-01

LACIE using techniques developed from the southern Great Plains drought analysis indicated the potential for drought damage in South Dakota. This potential was monitored and as it became apparent that a drought was developing, LACIE implemented some of the procedures used in the southern Great Plains drought. The technical approach used in South Dakota involved the normal use of LACIE sample segments (5 x 6 nm) every 18 days. Full frame color transparencies (100 x 100 nm) were used on 9 day intervals to identify the drought area and to track overtime. The green index number (GIN) developed using the Kauth transformation was computed for all South Dakota segments and selected North Dakota segments. A scheme for classifying segments as drought affected or not affected was devised and tested on all available 1976 South Dakota data. Yield model simulations were run for all CRD's Crop Reporting District) in South Dakota.

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

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.

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.

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

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.

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.

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 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

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.

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

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.

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

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.

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

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

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

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.

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

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

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

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

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.

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

Leaf Area Index Drives Soil Water Availability and Extreme Drought-Related Mortality under Elevated CO2 in a Temperate Grassland Model System

PubMed Central

Manea, Anthony; Leishman, Michelle R.

2014-01-01

The magnitude and frequency of climatic extremes, such as drought, are predicted to increase under future climate change conditions. However, little is known about how other factors such as CO2 concentration will modify plant community responses to these extreme climatic events, even though such modifications are highly likely. We asked whether the response of grasslands to repeat extreme drought events is modified by elevated CO2, and if so, what are the underlying mechanisms? We grew grassland mesocosms consisting of 10 co-occurring grass species common to the Cumberland Plain Woodland of western Sydney under ambient and elevated CO2 and subjected them to repeated extreme drought treatments. The 10 species included a mix of C3, C4, native and exotic species. We hypothesized that a reduction in the stomatal conductance of the grasses under elevated CO2 would be offset by increases in the leaf area index thus the retention of soil water and the consequent vulnerability of the grasses to extreme drought would not differ between the CO2 treatments. Our results did not support this hypothesis: soil water content was significantly lower in the mesocosms grown under elevated CO2 and extreme drought-related mortality of the grasses was greater. The C4 and native grasses had significantly higher leaf area index under elevated CO2 levels. This offset the reduction in the stomatal conductance of the exotic grasses as well as increased rainfall interception, resulting in reduced soil water content in the elevated CO2 mesocosms. Our results suggest that projected increases in net primary productivity globally of grasslands in a high CO2 world may be limited by reduced soil water availability in the future. PMID:24632832

Leaf area index drives soil water availability and extreme drought-related mortality under elevated CO2 in a temperate grassland model system.

PubMed

Manea, Anthony; Leishman, Michelle R

2014-01-01

The magnitude and frequency of climatic extremes, such as drought, are predicted to increase under future climate change conditions. However, little is known about how other factors such as CO2 concentration will modify plant community responses to these extreme climatic events, even though such modifications are highly likely. We asked whether the response of grasslands to repeat extreme drought events is modified by elevated CO2, and if so, what are the underlying mechanisms? We grew grassland mesocosms consisting of 10 co-occurring grass species common to the Cumberland Plain Woodland of western Sydney under ambient and elevated CO2 and subjected them to repeated extreme drought treatments. The 10 species included a mix of C3, C4, native and exotic species. We hypothesized that a reduction in the stomatal conductance of the grasses under elevated CO2 would be offset by increases in the leaf area index thus the retention of soil water and the consequent vulnerability of the grasses to extreme drought would not differ between the CO2 treatments. Our results did not support this hypothesis: soil water content was significantly lower in the mesocosms grown under elevated CO2 and extreme drought-related mortality of the grasses was greater. The C4 and native grasses had significantly higher leaf area index under elevated CO2 levels. This offset the reduction in the stomatal conductance of the exotic grasses as well as increased rainfall interception, resulting in reduced soil water content in the elevated CO2 mesocosms. Our results suggest that projected increases in net primary productivity globally of grasslands in a high CO2 world may be limited by reduced soil water availability in the future.

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.

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.

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.

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

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.

The ambiguity of drought events, a bottleneck for Amazon forest drought response modelling

NASA Astrophysics Data System (ADS)

De Deurwaerder, Hannes; Verbeeck, Hans; Baker, Timothy; Christoffersen, Bradley; Ciais, Philippe; Galbraith, David; Guimberteau, Matthieu; Kruijt, Bart; Langerwisch, Fanny; Meir, Patrick; Rammig, Anja; Thonicke, Kirsten; Von Randow, Celso; Zhang, Ke

2016-04-01

Considering the important role of the Amazon forest in the global water and carbon cycle, the prognosis of altered hydrological patterns resulting from climate change provides strong incentive for apprehending the direct implications of drought on the vegetation of this ecosystem. Dynamic global vegetation models have the potential of providing a useful tool to study drought impacts on various spatial and temporal scales. This however assumes the models being able to properly represent drought impact mechanisms. But how well do the models succeed in meeting this assumption? Within this study meteorological driver data and model output data of 4 different DGVMs, i.e. ORCHIDEE, JULES, INLAND and LPGmL, are studied. Using the palmer drought severity index (PDSI) and the mean cumulative water deficit (MWD), temporal and spatial representation of drought events are studied in the driver data and are referenced to historical extreme drought events in the Amazon. Subsequently, within the resulting temporal and spatial frame, we studied the drought impact on the above ground biomass (AGB) and gross primary production (GPP) fluxes. Flux tower data, field inventory data and the JUNG data-driven GPP product for the Amazon region are used for validation. Our findings not only suggest that the current state of the studied DGVMs is inadequate in representing Amazon droughts in general, but also highlights strong inter-model differences in drought responses. Using scatterplot-studies and input-output correlations, we provide insight in the origin of these encountered inter-model differences. In addition, we present directives of model development and improvement in scope of Amazon forest drought response modelling.

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.

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.

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

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

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

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

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.

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.

Drought-Tolerant Corn Hybrids Yield More in Drought-Stressed Environments with No Penalty in Non-stressed Environments

PubMed Central

Adee, Eric; Roozeboom, Kraig; Balboa, Guillermo R.; Schlegel, Alan; Ciampitti, Ignacio A.

2016-01-01

The potential benefit of drought-tolerant (DT) corn (Zea mays L.) hybrids may depend on drought intensity, duration, crop growth stage (timing), and the array of drought tolerance mechanisms present in selected hybrids. We hypothesized that corn hybrids containing DT traits would produce more consistent yields compared to non-DT hybrids in the presence of drought stress. The objective of this study was to define types of production environments where DT hybrids have a yield advantage compared to non-DT hybrids. Drought tolerant and non-DT hybrid pairs of similar maturity were planted in six site-years with different soil types, seasonal evapotranspiration (ET), and vapor pressure deficit (VPD), representing a range of macro-environments. Irrigation regimes and seeding rates were used to create several micro-environments within each macro-environment. Hybrid response to the range of macro and micro-environmental stresses were characterized in terms of water use efficiency, grain yield, and environmental index. Yield advantage of DT hybrids was positively correlated with environment ET and VPD. Drought tolerant hybrids yielded 5 to 7% more than non-DT hybrids in high and medium ET environments (>430 mm ET), corresponding to seasonal VPD greater than 1200 Pa. Environmental index analysis confirmed that DT hybrids were superior in stressful environments. Yield advantage for DT hybrids appeared as yield dropped below 10.8 Mg ha-1 and averaged as much as 0.6–1 Mg ha-1 at the low yield range. Hybrids with DT technology can offer a degree of buffering against drought stress by minimizing yield reduction, but also maintaining a comparable yield potential in high yielding environments. Further studies should focus on the physiological mechanisms presented in the commercially available corn drought tolerant hybrids. PMID:27790237

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

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

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

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

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

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

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

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

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

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

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'.

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

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

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

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.

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

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

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.

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.

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.

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

Monitoring of Drought Events in Gorontalo Regency

NASA Astrophysics Data System (ADS)

Koem, S.; Rusiyah

2017-12-01

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

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

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.

Performance index: An expeditious tool to screen for improved drought resistance in the Lathyrus genus.

PubMed

Silvestre, Susana; Araújo, Susana de Sousa; Vaz Patto, Maria Carlota; Marques da Silva, Jorge

2014-07-01

Some species of the Lathyrus genus are among the most promising crops for marginal lands, with high resilience to drought, flood, and fungal diseases, combined with high yields and seed nutritional value. However, lack of knowledge on the mechanisms underlying its outstanding performance and methodologies to identify elite genotypes has hampered its proper use in breeding. Chlorophyll a fast fluorescence transient (JIP test), was used to evaluate water deficit (WD) resistance in Lathyrus genus. Our results reveal unaltered photochemical values for all studied genotypes showing resistance to mild WD. Under severe WD, two Lathyrus sativus genotypes showed remarkable resilience maintaining the photochemical efficiency, contrary to other genotypes studied. Performance index (PIABS) is the best parameter to screen genotypes with improved performance and grain production under WD. Moreover, we found that JIP indices are good indicators of genotypic grain production under WD. Quantum yield of electron transport (ϕEo) and efficiency with which trapped excitons can move electrons further than QA (ψ0) revealed as important traits related to improved photosynthetic performance and should be exploited in future Lathyrus germplasm improvements. The JIP test herein described showed to be an expeditious tool to screen and to identify elite genotypes with improved drought resistance.

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

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.

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

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.

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...

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

NASA Astrophysics Data System (ADS)

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

2016-10-01

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

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.

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.

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.

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

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.

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.

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.

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.

The characteristics of drought occurrence in North Korea and its comparison with drought in South Korea

NASA Astrophysics Data System (ADS)

Lee, Bo-Ra; Oh, Su-Bin; Byun, Hi-Ryong

2015-07-01

The characteristics of the drought occurrence in North Korea over a period of 56 years (1952-2007) were analyzed by region, compared with those of South Korea, and graphed as a drought map for easy detection of the drought's history. To assess them, the Effective Drought Index (EDI), which was calculated from the daily precipitation data for 109 grids of the Korean Peninsula, was used. The daily precipitation data were extracted from the Asian Precipitation Highly Resolved Observational Data Integration towards Evaluation of Water Resources (APHRODITE). The characteristics of the drought occurrence in North Korea were summed up in the following five points. First, North Korea was divided into four drought sub-regions: the Northeastern region (G1), the Northern region (G2), the Central region (G3), and the Southern region (G4). Second, droughts occurred most frequently in G1 (28) and G4 (28 events) and least frequently in G3 (15 events). Third, in all sub-regions, short-term droughts lasting less than 100 days were the most frequent (53 % or higher) and the longest drought lasted 2,911 days (June 30, 1973 to June 20, 1981), which occurred in G3. Fourth, short-term droughts occurred mainly in spring, mid-term droughts (100-500 days) in spring and summer, and long-term droughts (over 500 days) in summer. Fifth, a dry period (monthly mean EDI <0) appeared in all sub-regions between 1973 and 1981 and between 1990 and 1993, and a strong negative precipitation anomaly appeared during each of these periods. When compared to the droughts in South Korea, those in North Korea were less frequent, but the mean duration was longer. Until 1979, droughts occurred almost at the same time in North Korea as South Korea, but beginning in 1980, the time differences between two regions became larger. Thus, the characteristics of the drought occurrence in North and South Korea differ.

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

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

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.

Impact of drought on wildfires in Iberia

NASA Astrophysics Data System (ADS)

Russo, Ana; Gouveia, Célia M.; DaCamara, Carlos; Sousa, Pedro; Trigo, Ricardo M.

2015-04-01

Southern European countries, and the Iberian Peninsula (IP) in particular, have been vastly affected by summer wildfires (Trigo et al., 2013). This condition is hampered by the frequent warm and dry meteorological conditions found in summer which play a significant role in the triggering and spreading of wildfires. These meteorological conditions are also particularly important for the onset and end of drought periods, a phenomenon that has recurrently affected the IP (Gouveia et al., 2012). Moreover, the IP corresponds to one of the most sensitive areas to current and future climate change, and recent and future trends towards a dryer and warmer Mediterranean climate (Sousa et al., 2014) will tend to exacerbate these problems. The main scope of this study was to investigate the impact of drought on wildfires' burned areas in the IP. The objective was to examine the correlation between drought, as expressed by both the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI) (Vicente-Serrano et al., 2010), and wildfire burned areas. The SPI and SPEI were both calculated for 4 large regions (Northwestern, Northern, Southwestern and Eastern) whose spatial patterns and seasonal fire regimes were shown to be related with constraining factors such as topography, vegetation cover and climate conditions (Trigo et al., 2013). In this study, the drought indices were determined for the time scales of 3 and 6 months for August and for 12 months in September, thus representing the summer and annual drought. The correlation between drought and burned areas during July and August was particularly significant for the 3 months SPEI and SPI relatively to the 6 and 12 time scales, which indicates that drought and fires relation is a small-size scale process. Moreover, the correlation between drought and burned areas during July and August was particularly significant for the Northern and Southwestern regions both for SPEI for 3 and 6

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).

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

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

The drought risk of maize in the farming-pastoral ecotone in Northern China based on physical vulnerability assessment

NASA Astrophysics Data System (ADS)

Wang, Zhiqiang; Jiang, Jingyi; Ma, Qing

2016-12-01

Climate change is affecting every aspect of human activities, especially the agriculture. In China, extreme drought events caused by climate change have posed a great threat to food safety. In this work we aimed to study the drought risk of maize in the farming-pastoral ecotone in Northern China based on physical vulnerability assessment. The physical vulnerability curve was constructed from the relationship between drought hazard intensity index and yield loss rate. The risk assessment of agricultural drought was conducted from the drought hazard intensity index and physical vulnerability curve. The probability distribution of drought hazard intensity index decreased from south-west to north-east and increased from south-east to north-west along the rainfall isoline. The physical vulnerability curve had a reduction effect in three parts of the farming-pastoral ecotone in Northern China, which helped to reduce drought hazard vulnerability on spring maize. The risk of yield loss ratio calculated based on physical vulnerability curve was lower compared with the drought hazard intensity index, which suggested that the capacity of spring maize to resist and adapt to drought is increasing. In conclusion, the farming-pastoral ecotone in Northern China is greatly sensitive to climate change and has a high probability of severe drought hazard. Risk assessment of physical vulnerability can help better understand the physical vulnerability to agricultural drought and can also promote measurements to adapt to climate change.

The extreme drought episode of August 2011-May 2012: A scenario for future droughts in Central Europe?

NASA Astrophysics Data System (ADS)

Zahradníček, P.; Trnka, M.; Brázdil, R.; Mozny, M.; Stepanek, P.; Hlavinka, P.; Malý, A.; Dubrovsky, M.

2014-12-01

The weather conditions from August 2011 to May 2012 produced an extreme drought in the eastern Czech Republic (Moravia), whereas the patterns were nearly normal in its western region (Bohemia). The Southern and Central Moravia regions, which represent the most important agricultural areas, were most affected by the drought. The precipitation totals for the studied period were 50% to 70% of the long-term mean, which was calculated for 1961-2000. In autumn 2011, the total precipitation accounted for 10% to 30% of the long-term mean for most of Moravia, increasing to 30% to 50% in spring 2012. Moreover, 7.5% of the Czech Republic experienced a 100-year drought; 20% of the country experienced a 20-year drought. According to the Palmer Drought Severity Index, the 2012 drought was classified as the worst in the past 130 years. The drought patterns were related to the prevailing high-pressure systems over Central Europe and the occurrence of weather types with different precipitation amounts in Bohemia and Moravia. The most substantial drought effects occurred in the agricultural sector. A decrease in cereal yields was observed in the analyzed production areas in Moravia, which was unprecedented in the past 52 years. Moreover, winter crops were affected more than spring crops. An increased risk of fire occurred due to the drought conditions; the largest forest fire in the past 15 years was recorded during this period. Furthermore, signs of hydrological drought were also reported in rivers. The 2011-2012 drought was compared with the significant droughts in 2000, 2003 and 2007. Austria and Slovakia, which neighbor the Czech Republic, experienced a similar drought. This drought analysis can be used as a scenario for future droughts and their impacts in Central Europe due to the global warming projected by GCMs.Acknowledgements:This study was made possible by the generous support of the "Establishment of International Scientific Team Focused on Drought Research" project (no

Drought timing influences the legacy of tree growth recovery.

PubMed

Huang, Mengtian; Wang, Xuhui; Keenan, Trevor F; Piao, Shilong

2018-05-04

Whether and how the timing of extreme events affects the direction and magnitude of legacy effects on tree growth is poorly understood. In this study, we use a global database of Ring-Width Index (RWI) from 2,500 sites to examine the impact and legacy effects (the departure of observed RWI from expected RWI) of extreme drought events during 1948-2008, with a particular focus on the influence of drought timing. We assessed the recovery of stem radial growth in the years following severe drought events with separate groupings designed to characterize the timing of the drought. We found that legacies from extreme droughts during the dry season (DS droughts) lasted longer and had larger impacts in each of the 3 years post drought than those from extreme droughts during the wet season (WS droughts). At the global scale, the average integrated legacy from DS droughts (0.18) was about nine times that from WS droughts (0.02). Site-level comparisons also suggest stronger negative impacts or weaker positive impacts of DS droughts on tree growth than WS droughts. Our results, therefore, highlight that the timing of drought is a crucial factor determining drought impacts on tree recovery. Further increases in baseline aridity could therefore exacerbate the impact of punctuated droughts on terrestrial ecosystems. © 2018 John Wiley & Sons Ltd.

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.

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.

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

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.

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.

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.

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

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.

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.

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

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.

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.

Precursor conditions related to Zimbabwe's summer droughts

NASA Astrophysics Data System (ADS)

Nangombe, Shingirai; Madyiwa, Simon; Wang, Jianhong

2018-01-01

Despite the increasing severity of droughts and their effects on Zimbabwe's agriculture, there are few tools available for predicting these droughts in advance. Consequently, communities and farmers are more exposed, and policy makers are always ill prepared for such. This study sought to investigate possible cycles and precursor meteorological conditions prior to drought seasons that could be used to predict impending droughts in Zimbabwe. The Single Z-Index was used to identify and grade drought years between 1951 and 2010 according to rainfall severity. Spectral analysis was used to reveal the cycles of droughts for possible use of these cycles for drought prediction. Composite analysis was used to investigate circulation and temperature anomalies associated with severe and extreme drought years. Results indicate that severe droughts are more highly correlated with circulation patterns and embedded weather systems in the Indian Ocean and equatorial Pacific Ocean than any other area. This study identified sea surface temperatures in the average period June to August, geopotential height and wind vector in July to September period, and air temperature in September to November period as precursors that can be used to predict a drought occurrence several months in advance. Therefore, in addition to sea surface temperature, which was identified through previous research for predicting Zimbabwean droughts, the other parameters identified in this study can aid in drought prediction. Drought cycles were established at 20-, 12.5-, 3.2-, and 2.7-year cycles. The spectral peaks, 12.5, 3.2, and 2.7, had a similar timescale with the luni-solar tide, El Niño Southern Oscillation and Quasi Biennial Oscillation, respectively, and hence, occurrence of these phenomena have a possibility of indicating when the next drought might be.

Past and future drought in Mongolia.

PubMed

Hessl, Amy E; Anchukaitis, Kevin J; Jelsema, Casey; Cook, Benjamin; Byambasuren, Oyunsanaa; Leland, Caroline; Nachin, Baatarbileg; Pederson, Neil; Tian, Hanqin; Hayles, Laia Andreu

2018-03-01

The severity of recent droughts in semiarid regions is increasingly attributed to anthropogenic climate change, but it is unclear whether these moisture anomalies exceed those of the past and how past variability compares to future projections. On the Mongolian Plateau, a recent decade-long drought that exceeded the variability in the instrumental record was associated with economic, social, and environmental change. We evaluate this drought using an annual reconstruction of the Palmer Drought Severity Index (PDSI) spanning the last 2060 years in concert with simulations of past and future drought through the year 2100 CE. We show that although the most recent drought and pluvial were highly unusual in the last 2000 years, exceeding the 900-year return interval in both cases, these events were not unprecedented in the 2060-year reconstruction, and events of similar duration and severity occur in paleoclimate, historical, and future climate simulations. The Community Earth System Model (CESM) ensemble suggests a drying trend until at least the middle of the 21st century, when this trend reverses as a consequence of elevated precipitation. Although the potential direct effects of elevated CO 2 on plant water use efficiency exacerbate uncertainties about future hydroclimate trends, these results suggest that future drought projections for Mongolia are unlikely to exceed those of the last two millennia, despite projected warming.

Past and future drought in Mongolia

PubMed Central

Hessl, Amy E.; Anchukaitis, Kevin J.; Jelsema, Casey; Cook, Benjamin; Byambasuren, Oyunsanaa; Leland, Caroline; Nachin, Baatarbileg; Pederson, Neil; Tian, Hanqin; Hayles, Laia Andreu

2018-01-01

The severity of recent droughts in semiarid regions is increasingly attributed to anthropogenic climate change, but it is unclear whether these moisture anomalies exceed those of the past and how past variability compares to future projections. On the Mongolian Plateau, a recent decade-long drought that exceeded the variability in the instrumental record was associated with economic, social, and environmental change. We evaluate this drought using an annual reconstruction of the Palmer Drought Severity Index (PDSI) spanning the last 2060 years in concert with simulations of past and future drought through the year 2100 CE. We show that although the most recent drought and pluvial were highly unusual in the last 2000 years, exceeding the 900-year return interval in both cases, these events were not unprecedented in the 2060-year reconstruction, and events of similar duration and severity occur in paleoclimate, historical, and future climate simulations. The Community Earth System Model (CESM) ensemble suggests a drying trend until at least the middle of the 21st century, when this trend reverses as a consequence of elevated precipitation. Although the potential direct effects of elevated CO2 on plant water use efficiency exacerbate uncertainties about future hydroclimate trends, these results suggest that future drought projections for Mongolia are unlikely to exceed those of the last two millennia, despite projected warming. PMID:29546236

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.

Observed evolution of drought episodes assessed with the Standardized Precipitation Evapotranspiration Index (SPEI) over the Czech Republic

NASA Astrophysics Data System (ADS)

Potop, V.; Boroneana, C.; Mozny, M.; Stepanek, P.; Skalak, P.

2012-04-01

This paper investigates the spatial and temporal evolution of drought episodes assessed with the Standardized Precipitation Evapotranspiration Index (SPEI) over the Czech Republic. The SPEI were calculated from monthly records of mean temperature and precipitation totals using a dense network of 183 climatological stations for the period 1961-2010. The SPEI were calculated with various lags, 1, 3, 6, 12 and 24 months. The drought at these time scales is relevant for agricultural, hydrological and socio-economic impact, respectively. The study refers at the warm season of the year (April to September). The principal modes of variability of these five time scale SPEI were identified using the analysis of Empirical Orthogonal Functions (EOF). The explained variance of the leading EOF ranges between 71 and 61% as the time scale for calculating the SPEI increases from 1 month to 24 months. The explained variance of EOF2 and EOF3 ranges between 5 to 9% and 4 to 6%, respectively, as the SPEI is calculated for 1 to 24 months. Based on the spatial distribution of the EOF2 and EOF3 for all time scales of SPEI, which correspond to some extend to a regionalization previously used in other studies, we identified three climatically homogeneous regions, corresponding to the altitudes below 400 m, between 401 and 700 m and, above 700 m. These regions correspond to different land use types with mostly intensive agriculture, less intensive agriculture and limited agricultural production and mostly forested, respectively. For these three regions the frequency distribution of the SPEI values in 7 classes of drought category (%) were calculated based on station records in each region. The normal conditions represent around 65% out of the total values of SPEI for all times scales, in all three regions, while moderate drought and moderate wet conditions are almost equally distributed around 10.5 %. Differences in extremely dry conditions (5%) compared to extremely wet conditions (1

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.

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.

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

Comparison of Agricultural Drought Indicators over West Africa

NASA Astrophysics Data System (ADS)

Husak, G. J.; Turner, W.; McNally, A.; Shukla, S.; Funk, C. C.

2017-12-01

The Famine Early Warning Systems Network (FEWS NET) monitors critical environmental variables that impact food production in developing countries, including over 30 countries in Africa. Much of this work focuses on the identification of agricultural drought using remotely sensed and modeled estimates of conditions. These variables estimate precipitation, potential evapotranspiration, water availability for crops and soil moisture - among others - at a critical time, or accumulated over intervals within the season. Frequently, these variables are used in a "convergence of evidence" approach to identify the location and severity of agricultural drought over a region. While much work has gone into identifying and calculating these key indicators, little attention has been given to the relationships between these variables. This work explores the relationship between four key agricultural drought indicators over West Africa to determine the extent to which they are providing unique information and also to expose where certain variables may not be adding independent information to the identification of agricultural drought and the potential for food insecurity. These variables investigated in this study are the Standardized Precipitation Index (SPI), the Standardized Precipitation Evapotranspiration Index (SPEI), the Water Requirement Satisfaction Index (WRSI) and modeled soil moisture (SM) from the FEWSNET Land Data Assimilation System (FLDAS). We look at 35 years of data (1982-2016) over West Africa and identify the primary growing season for the region, then compare the four variables above during this prime season. Because the computational costs of calculating these different indicators varies, we seek to identify where products that are less cost/data intensive adequately capture the same information as the more intensive indicators. The outcome highlights where particular products are most useful for the identification of agricultural drought over the region.

Remote sensing of drought and salinity stressed turfgrass

NASA Astrophysics Data System (ADS)

Ikemura, Yoshiaki

The ability to detect early signs of stress in turfgrass stands using a rapid, inexpensive, and nondestructive method would be a valuable management tool. Studies were conducted to determine if digital image analysis and spectroradiometric readings obtained from drought- and salinity-stressed turfgrasses accurately reflected the varying degrees of stress and correlated strongly with visual ratings, relative water content (RWC) and leaf osmolality, standard methods for measuring stress in plants. Greenhouse drought and salinity experiments were conducted on hybrid bluegrass [Poa arachnifera (Torn.) x pratensis (L.)] cv. Reveille and bermudagrass [Cynodon dactylon (L.)] cv. Princess 77. Increasing drought and salinity stress led to decreased RWC, increased leaf osmolality, and decreased visual ratings for both species. Percent green cover and hue values obtained from digital image analysis, and Normalized Difference Vegetation Index (NDVI), calculated from spectroradiometric readings, were moderately to highly correlated with visual ratings, RWC, and leaf osmolality. Similarly, in a field validation study conducted on hybrid bluegrass, spectral reflectance ratios were moderately to highly correlated with visual ratings. In addition, percent green cover obtained from digital image analysis was strongly correlated with most of the spectral ratios, particularly the ratio of fluorescence peaks (r = -0.88 to -0.99), modified triangular vegetation index (MTVI) (r = 0.82 to 0.98), and NDVI (r = 0.84 to 0.99), suggesting that spectral reflectance and digital image analysis are equally effective at detecting changes in color brought on by stress. The two methods differed in their ability to distinguish between drought salinity stress. Hue values obtained from digital image analysis responded differently to increasing drought stress than to increasing salinity stress. Whereas the onset of drought stress was reflected by increased hue values followed by a decrease in values as

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

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

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

Attributing recent changes in droughts over China: 1961-2013

NASA Astrophysics Data System (ADS)

Sun, Fubao; Zhang, Jie; Xu, Jijun; Chen, Yaning; Sang, Yanfang; Liu, Changming

2016-04-01

It is controversial how droughts respond to global warming for the commonly used drought index: the Palmer Drought Severity Index (PDSI). Here we assess recent changes in the droughts over China (1961-2013) using the PDSI with two different estimates, i.e., the Thornthwaite (PDSI_th) and Penman-Monteith (PDSI_pm) approaches. We found that droughts have become more severe in the PDSI_th but slightly lessened in the PDSI_pm estimate. To quantify and attribute that difference in the PDSI_th and PDSI_pm, we designed numerical experiments and found that drying trend of the PDSI_th responding to the global warming alone is 3.4 times higher than that of the PDSI_pm, and the latter was further compensated by decreases in wind speed and solar radiation causing the slightly wetting in the PDSI_pm. Interestingly, we found that inter-basin difference in the PDSI_th and PDSI_pm response to the global warming alone tends to be larger in warmer basins, exponentially depending on mean temperature. References: Zhang, J., F. Sun, J. Xu, Y. Chen, Y. Sang, and C. Liu (2016), Dependence of trends in and sensitivity of drought over China (1961-2013) on potential evaporation model, Geophys. Res. Lett., 43, doi:10.1002/2015GL067473. Sun, F. B., M. L. Roderick, and G. D. Farquhar (2012), Changes in the variability of global land precipitation, Geophys. Res. Lett., 39, L19402, doi: 10.1029/2012GL053369.

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.

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.

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.

Understanding the time-lag effect of terrestrial ecosystem response to drought: a regional case study of the 2000s Millennium Drought in Australia

NASA Astrophysics Data System (ADS)

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

2016-12-01

Drought is one of the major drivers of the reduction in terrestrial ecosystem productivity. Ecosystem productivity may not primarily be driven by present moisture conditions. Instead, earlier drought conditions may have the largest impact on vegetation growth. We investigate this time-lag effect in Australia by comparing MODIS NDVI data with multiple drought metrics that are sensitive to water deficits at different soil depths. These metrics include 1) soil moisture (SM) from microwave satellite-retrievals that is sensitive to top-centimeter SM variations; 2) the Palmer drought severity index (PDSI) which is sensitive to atmosphere moisture demand and shallow-depth ( 1 meter) SM changes; 3) the newly developed GRACE drought severity index (GRACE-DSI) that is sensitive to changes in overall terrestrial water storage component of the hydrologic cycle and complements satellite SM observations and the PDSI by providing information about deep groundwater storage changes. We quantify the temporal lags between NDVI and these drought metrics during 2002-2014. We find that the NDVI closely evolves with the GRACE-DSI but lags 1-3 months behind the PDSI and satellite-retrievals of SM in western Australia. This pattern however is reverse in eastern Australia. These contrasting NDVI response patterns indicate that vegetation in western Australia is more sensitive to water storage in relatively deeper soil depths than vegetation in the east. This suggests that, in western Australia, vegetation might experience a protracted recovery period after extreme drought since, usually, moisture recharge in deeper soil depths takes a relatively longer period. We conclude that the time-lag effect in Australia is associated with the relative depth of SM to which vegetation is most sensitive. We suggest that characterizing the relative vegetation moisture sensitive depth at the global scale is important for understanding the nature and pace of terrestrial ecosystem recovery from extreme

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

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

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

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

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.

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.

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

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

[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

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

Attributing changes in recent PDSI droughts over China

NASA Astrophysics Data System (ADS)

Sun, Fubao; Zhang, Jie; Liu, Wenbin; Ge, Quansheng

2017-04-01

Drought is a major natural hazard measured by water availability significantly below normal conditions for a region. Because of great socioeconomic significance, the occurrence of disastrous droughts has received enormous public attention and discussion including, for example, the recent prominent California droughts in 2011-2015 and the once-in-a-century droughts in southwest China (2009 continuing to now). How droughts change in the past and its attribution are grand scientific questions to be addressed under global climate change. By theory, drought is determined by the balance between precipitation and atmospheric evaporative demand and is further complicated by such as vegetation. To describe the droughts over China (1961-2013), we use the widely used Palmer Drought Severity Index (PDSI), that was forced by two different estimates of evaporative demand, i.e., the Thornthwaite (PDSI_th) and Penman-Monteith (PDSI_pm). We found that droughts have become more severe in the PDSI_th but slightly lessened in the PDSI_pm estimate. To quantify and interpret the different responses in the PDSI_th and PDSI_pm, we designed numerical experiments and found that drying trend of the PDSI_th responding to the warming alone is 3.4 times higher than that of the PDSI_pm, and the latter was further compensated by decreases in wind speed and solar radiation causing the slightly wetting in the PDSI_pm.

Drought impacts and resilience on crops via evapotranspiration estimations

NASA Astrophysics Data System (ADS)

Timmermans, Joris; Asadollahi Dolatabad, Saeid

2015-04-01

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.

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.

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

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.

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

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

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.

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

NASA Astrophysics Data System (ADS)

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

2009-12-01

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

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.

Hydrological Drought in the Anthropocene: Impacts of Local Water Extraction and Reservoir Regulation in the U.S.: Hydrological Drought in the Anthropocene

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

Wan, Wenhua; Zhao, Jianshi; Li, Hong-Yi

Hydrological drought is a substantial negative deviation from normal hydrologic conditions and is influenced by climate and human activities such as water management. By perturbing the streamflow regime, climate change and water management may significantly alter drought characteristics in the future. Here we utilize a high-resolution integrated modeling framework that represents water management in terms of both local surface water extraction and reservoir regulation, and use the Standardized Streamflow Index (SSI) to quantify hydrological drought. We explore the impacts of water management on hydrological drought over the contiguous US in a warming climate with and without emissions mitigation. Despite themore » uncertainty of climate change impacts, local surface water extraction consistently intensifies drought that dominates at the regional to national scale. However, reservoir regulation alleviates drought by enhancing summer flow downstream of reservoirs. The relative dominance of drought intensification or relief is largely determined by the water demand, with drought intensification dominating in regions with intense water demand such as the Great Plains and California, while drought relief dominates in regions with low water demand. At the national level, water management increases the spatial extent of extreme drought despite some alleviations of moderate to severe drought. In an emissions mitigation scenario with increased irrigation demand for bioenergy production, water management intensifies drought more than the business-as-usual scenario at the national level, so the impacts of emissions mitigation must be evaluated by considering its benefit in reducing warming and evapotranspiration against its effects on increasing water demand and intensifying drought.« less

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

Dendroclimatic estimates of a drought index for northern Virginia

USGS Publications Warehouse

Puckett, Larry J.

1981-01-01

A 230-year record of the Palmer drought-severity index (PDSI) was estimated for northern Virginia from variations in widths of tree rings. Increment cores were extracted from eastern hemlock, Tsuga canadensis (L.) Carr., at three locations in northern Virginia. Measurements of annual growth increments were made and converted to standardized indices of growth. A response function was derived for hemlock to determine the growth-climate relationship. Growth was positively correlated with precipitation and negatively correlated with temperature during the May-July growing season. Combined standardized indices of growth were calibrated with the July PDSI. Growth accounted for 20-30 percent of the PDSI variance. Further regressions using factor scores of combined tree growth indices resulted in a small but significant improvement. Greatest improvement was made by using factor scores of growth indices of individual trees, thereby accounting for 64 percent of the July PDSI variance in the regression. Comparison of the results with a 241-year reconstruction from New York showed good agreement between low-frequency climatic trends. Analysis of the estimated Central Mountain climatic division of Virginia PDSI record indicated that, relative to the long-term record (1746-1975), dry years have occurred in disproportionally larger numbers during the last half of the 19th century and the mid-20th century. This trend appears reversed for the last half of the 18th century and the first half of the 19th century. Although these results are considered first-generation products, they are encouraging, suggesting that once additional tree-ring chronologies are constructed and techniques are refined, it will be possible to obtain more accurate estimates of prior climatic conditions in the mid-Atlantic region.

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.

Drought

Treesearch

John W. Coulston

2009-01-01

Drought occurrence is a function of temperature, moisture, and soil characteristics. In some regions, such as much of the Western United States, drought is a regular occurrence, while in others, such as the Northeastern United States, drought occurs on an irregular basis. Moderate drought stress tends to slow plant growth while severe drought stress also reduces...

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...

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

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...

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.

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.

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.

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

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 differences in drought vulnerability

NASA Astrophysics Data System (ADS)

Perčec Tadić, M.; Cindić, K.; Gajić-Čapka, M.; Zaninović, K.

2012-04-01

Drought causes the highest economic losses among all hydro-meteorological events in Croatia. It is the most frequent hazard, which produces the highest damages in the agricultural sector. The climate assessment in Croatia according to the aridity index (defined as the ratio of precipitation and potential evapotranspiration) shows that the susceptibility to desertification is present in the warm part of the year and it is mostly pronounced in the Adriatic region and the eastern Croatia lowland. The evidence of more frequent extreme drought events in the last decade is apparent. These facts were motivation to study the drought risk assessment in Croatia. One step in this issue is the construction of the vulnerability map. This map is a complex combination of the geomorphologic and climatological inputs (maps) that are presumed to be natural factors which modify the amount of moisture in the soil. In this study, the first version of the vulnerability map is followed by the updated one that additionally includes the soil types and the land use classes. The first input considered is the geomorphologic slope angle calculated from the digital elevation model (DEM). The SRTM DEM of 100 m resolution is used. The steeper slopes are more likely to lose water and to become dryer. The second climatological parameter, the solar irradiation map, gives for the territory of Croatia the maximum irradiation on the coast. The next meteorological parameter that influences the drought vulnerability is precipitation which is in this assessment included through the precipitation variability expressed by the coefficient of variation. Larger precipitation variability is related with the higher drought vulnerability. The preliminary results for Croatia, according to the recommended procedure in the framework of Drought Management Centre for Southeastern Europe (DMCSEE project), show the most sensitive areas to drought in the southern Adriatic coast and eastern continental lowland.

Species biogeography predicts drought responses in a seasonally dry tropical forest

NASA Astrophysics Data System (ADS)

Schwartz, N.; Powers, J. S.; Vargas, G.; Xu, X.; Smith, C. M.; Brodribb, T.; Werden, L. K.; Becknell, J.; Medvigy, D.

2017-12-01

The timing, distribution, and amount of rainfall in the seasonal tropics have shifted in recent years, with consequences for seasonally dry tropical forests (SDTF). SDTF are sensitive to changing rainfall regimes and drought conditions, but sensitivity to drought varies substantially across species. One potential explanation of species differences is that species that experience dry conditions more frequently throughout their range will be better able to cope with drought than species from wetter climates, because species from drier climates will be better adapted to drought. An El-Niño induced drought in 2015 presented an opportunity to assess species-level differences in mortality in SDTF, and to ask whether the ranges of rainfall conditions species experience and the average rainfall regimes in species' ranges predict differences in mortality rates in Costa Rican SDTF. We used field plot data from northwest Costa Rica to determine species' level mortality rates. Mortality rates ranged substantially across species, with some species having no dead individuals to as high as 50% mortality. To quantify rainfall conditions across species' ranges, we used species occurrence data from the Global Biodiversity Information Facility, and rainfall data from the Chelsa climate dataset. We found that while the average and range of mean annual rainfall across species ranges did not predict drought-induced mortality in the field plots, across-range averages of the seasonality index, a measure of rainfall seasonality, was strongly correlated with species-level drought mortality (r = -0.62, p < 0.05), with species from more strongly seasonal climates experiencing less severe drought mortality. Furthermore, we found that the seasonality index was a stronger predictor of mortality than any individual functional trait we considered. This result shows that species' biogeography may be an important factor for how species will respond to future drought, and may be a more integrative

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.

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.

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.

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 ...

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.

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.

Understanding and Seasonal Forecasting of multiscale droughts in China

NASA Astrophysics Data System (ADS)

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

2016-12-01

Droughts were climate anomalies that occurred naturally. But they have been altered by climate change and human interventions, and have covered a variety of spatiotemporal scales from seasonal/decadal droughts at regional to continental scales that are associated with large-scale climate anomalies and certain atmospheric circulation patterns, to flash droughts at local scales that are usually concurrent with heat extremes. Droughts have quite different implications across a number of sectors, with the considerations augmented from meteorological droughts to agricultural and hydrological droughts, where the latter could be affected by human activities directly. This raises a grand challenge to understand and predict droughts across scales in a changing environment. This presentation will be started by diagnosing an El Niño-induced meteorological drought that occurred over northern China (NC) last year, where the oceanic and atmospheric background are investigated, and the real-time prediction from Climate Forecast System version 2 (CFSv2) are diagnosed. The comparison between 2015 NC drought and other historical droughts are discussed, and a dynamical-statistical forecasting approach is being developed. Secondly, a rapidly developing agricultural drought event that termed as "flash droughts" accompanied by extreme heat, low soil moisture and high evapotranspiration (ET), occurred frequently around the world, and caused devastating impacts on crop yields and water supply. The increasing trend of flash droughts over China was tripled after the big El Niño event in 1997/98, but the warming hiatus does exist over many regions of China. The changes in flash droughts over China are being attributed by using multiple reanalysis data and the CMIP5 simulations. Lastly, the effects of human interventions on the drought propagation will be investigated over Yellow River basin in northern China. A comparison between SPI and standardized streamflow index indicates that the

Advancing Drought Understanding, Monitoring and Prediction

NASA Technical Reports Server (NTRS)

Mariotti, Annarita; Schubert, Siegfried D.; Mo, Kingtse; Peters-Lidard, Christa; Wood, Andy; Pulwarty, Roger; Huang, Jin; Barrie, Dan

2013-01-01

Having the capacity to monitor droughts in near-real time and providing accurate drought prediction from weeks to seasons in advance can greatly reduce the severity of social and economic damage caused by drought, a leading natural hazard for North America. The congressional mandate to establish the National Integrated Drought Information System (NIDIS; Public Law 109-430) in 2006 was a major impulse to develop, integrate, and provide drought information to meet the challenges posed by this hazard. Significant progress has been made on many fronts. On the research front, efforts by the broad scientific community have resulted in improved understanding of North American droughts and improved monitoring and forecasting tools. We now have a better understanding of the droughts of the twentieth century including the 1930s "Dust Bowl"; we have developed a broader array of tools and datasets that enhance the official North American Drought Monitor based on different methodologies such as state-of-the-art land surface modeling (e.g., the North American Land Data Assimilation System) and remote sensing (e.g., the evaporative stress index) to better characterize the occurrence and severity of drought in its multiple manifestations. In addition, we have new tools for drought prediction [including the new National Centers for Environmental Prediction (NCEP) Climate Forecast System, version 2, for operational prediction and an experimental National Multimodel Ensemble] and have explored diverse methodologies including ensemble hydrologic prediction approaches. Broad NIDIS-inspired progress is influencing the development of a Global Drought Information System (GDIS) under the auspices of the World Climate Research Program. Despite these advances, current drought monitoring and forecasting capabilities still fall short of users' needs, especially the need for skillful and reliable drought forecasts at regional and local scales. To tackle this outstanding challenging problem

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

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.

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

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.

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

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

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

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

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

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...

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

What Caused the Winter Drought in Western Nepal during Recent Years?

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

Wang, S-Y; Yoon, Jin-Ho; Gillies, R.

Western Nepal has experienced consecutive and worsened winter drought conditions since 2000 culminating in a severe drought episode during 2008-2009. In this study, the meteorological conditons and a historical pespective of the winter droughts in western Nepal were analyzed using respectively instumental records and a paleoclimatic drought index. Althought decadal-scale drought conditions were found to be recurrent in the paleoclimate record, the severity of the recent decadal drought (since 2000) clearly stands out in the 700 years of record and, this is suggestive of potential anthropogenic influences in the recent decades. Meteorological diagnosis using atmospheric reanalysis in the recent decadesmore » revealed that (1) winter drought in western Nepal is linked to the Arctic Oscillation and its decadal variability, which initiates a tropospheric short-wave train across the Europe, Eurasia and South Asia, and that (2) the persistent warming of the Indian Ocean likely contributes to the suppression of rainfall through enhanced local Hadley circultion. It is therefore conceivable that the recent spells of decadal drought in Nepal drought are symptomatic of both natural variability and anthropogenic influences.« less

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

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