scholarly journals A hybrid drought index for drought assessment in Wadi Shueib catchment area in Jordan

2020 ◽  
Vol 22 (4) ◽  
pp. 937-956
Author(s):  
Odai Al Balasmeh ◽  
Richa Babbar ◽  
Tapas Karmaker
Keyword(s):  
Soil Moisture ◽  
Large Scale ◽  
Drought Index ◽  
Agricultural Drought ◽  
Wavelet Coherence ◽  
Sunspot Activity ◽  
Drought Indices ◽  
Entropy Weight ◽  
Drought Assessment ◽  
Near Future

Abstract Wadi Shueib catchment in Jordan is a water stress area and climate change is creating a further deficiency in precipitation, streamflow, and soil moisture; which are a deterrent to agriculture production in the area. In order to analyze the drought-like situation in the area, a hybrid drought index (HDI) has been developed considering the combined effect of these three variables. Fuzzy analytical hierarchy process (F-AHP) and entropy weight methods were carried out to develop a hybrid drought index (HDI) which combines meteorological, hydrological, and agricultural drought indices based on precipitation, streamflow, and soil moisture data in the area. The wavelet transform (WT) with cross wavelet (XCT) and wavelet coherence (WTC) were applied to investigate the interaction and the relations between the HDI index, drought indices, and large-scale sunspot activity Niño3.4 index. The results show that HDI can easily capture the trend of the drought-like conditions in the area based on the available data. The trend analysis of HDI revealed an increasing trend in the drought incidences in the near future. The study can be used as an early alarm for drought in the area, which can be helpful in the decision-making process towards water resources planning and management in the future.

scholarly journals Development and Evaluation of an Agricultural Drought Index by Harnessing Soil Moisture and Weather Data

Water ◽  
2019 ◽  
Vol 11 (7) ◽  
pp. 1375 ◽  
Author(s):  
Ali Ajaz ◽  
Saleh Taghvaeian ◽  
Kul Khand ◽  
Prasanna H. Gowda ◽  
Jerry E. Moorhead
Keyword(s):  
Soil Moisture ◽  
Crop Production ◽  
Drought Index ◽  
Root Zone ◽  
Correlation Coefficients ◽  
Meteorological Drought ◽  
Agricultural Drought ◽  
Weather Data ◽  
Drought Indices ◽  
Growth Stages

A new agricultural drought index was developed for monitoring drought impacts on agriculture in Oklahoma. This new index, called the Soil Moisture Evapotranspiration Index (SMEI), estimates the departure of aggregated root zone moisture from reference evapotranspiration. The SMEI was estimated at five locations across Oklahoma representing different climates. The results showed good agreement with existing soil moisture-based (SM) and meteorological drought indices. In addition, the SMEI had improved performance compared to other indices in capturing the effects of temporal and spatial variations in drought. The relationship with crop production is a key characteristic of any agricultural drought index. The correlations between winter wheat production and studied drought indices estimated during the growing period were investigated. The correlation coefficients were largest for SMEI (r > 0.9) during the critical crop growth stages when compared to other drought indices, and r decreased by moving from semi-arid to more humid regions across Oklahoma. Overall, the results suggest that the SMEI can be used effectively for monitoring the effects of drought on agriculture in Oklahoma.

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

2014 ◽  
Vol XL-8 ◽  
pp. 89-100 ◽  
Author(s):  
S. K. Padhee ◽  
B. R. Nikam ◽  
S. P. Aggarwal ◽  
V. Garg
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Land Surface ◽  
Drought Index ◽  
Meteorological Data ◽  
Vegetation Indices ◽  
Agricultural Drought ◽  
Predictive Capability ◽  
Drought Assessment ◽  
Soil Moisture Anomaly

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). <br><br> The key idea was to achieve the goal by utilizing the integrated scenarios from meteorological observations and soil moisture distribution. EDI condition maps were prepared from daily precipitation data recorded by Indian Meteorological Department (IMD), distributed within the study area. With the aid of frequent MODIS products viz. vegetation indices (VIs), and land surface temperature (LST), the coarse resolution soil moisture product from European Space Agency (ESA) were downscaled using linking model based on Triangle method to a finer resolution soil moisture product. EDI and spatially downscaled soil moisture products were later used with MODIS 16 days NDVI product as key elements to assess and predict agricultural drought in irrigated and rain-fed agricultural systems in Bundelkhand region of India. Meteorological drought, soil moisture deficiency and NDVI degradation were inhabited for each and every pixel of the image in GIS environment, for agricultural impact assessment at a 16 day temporal scale for Rabi seasons (October&ndash;April) between years 2000 to 2009. Based on the statistical analysis, good correlations were found among the parameters EDI and soil moisture anomaly; NDVI anomaly and soil moisture anomaly lagged to 16 days and these results were exploited for the development of a linear prediction model. The predictive capability of the developed model was validated on the basis of spatial distribution of predicted NDVI which was compared with MODIS NDVI product in the beginning of preceding Rabi season (Oct&ndash;Dec of 2010).The predictions of the model were based on future meteorological data (year 2010) and were found to be yielding good results. The developed model have good predictive capability based on future meteorological data (rainfall data) availability, which enhances its utility in analyzing future Agricultural conditions if meteorological data is available.

scholarly journals EVALUATION OF THE SOIL MOISTURE AGRICULTURAL DROUGHT INDEX (SMADI) AND PRECIPITATION-BASED DROUGHT INDICES IN ARGENTINA

2020 ◽  
Vol IV-3/W2-2020 ◽  
pp. 53-58
Author(s):  
M. M. Salvia ◽  
N. Sánchez ◽  
M. Piles ◽  
A. Gonzalez-Zamora ◽  
J. Martínez-Fernández
Keyword(s):  
Soil Moisture ◽  
Gross Domestic Product ◽  
Surface Temperature ◽  
Drought Index ◽  
Standardized Precipitation Index ◽  
Agricultural Drought ◽  
Drought Indices ◽  
Agricultural Exports ◽  
Hydric Stress ◽  
The Standardized Precipitation Index

Abstract. Agricultural drought is one of the most critical hazards with regard to intensity, severity, frequency, spatial extension and impact on livelihoods. This is especially true for Argentina, where agricultural exports can represent up to 10% of gross domestic product (GDP), and where drought events for 2018 led to a decrease of nearly 0.5% of GDP. In this work, we investigate the applicability of the Soil Moisture Agricultural Drought Index (SMADI) for detection of droughts in Argentina, and compare its performance with the use of two well-known precipitation-based indices: the Standardized Precipitation Index (SPI) and the Standardized Precipitation- Evaporation Index (SPEI). SMADI includes satellite-based information of soil moisture, surface temperature and vegetation greenness, and was designed to capture the hydric stress on the soil-vegetation ensemble. Results indicate that SMADI has greater capabilities for agricultural drought detection than SPI and SPEI: it was able to recognize more than 83% of the registered emergencies, correctly classifying 75% of them as extreme droughts, and outperforming SPI and SPEI in all the analyzed metrics.

Development of a Next Generation Drought Index: combining multiple global and local data sources to enable detection of sector-specific drought impacts

2021 ◽  
Author(s):  
Dimmie Hendriks ◽  
Pieter Hazenberg ◽  
Jonas Gotte ◽  
Patricia Trambauer ◽  
Arjen Haag ◽  
...  
Keyword(s):  
Drought Index ◽  
Agricultural Drought ◽  
Data Sources ◽  
Drought Indices ◽  
Next Generation ◽  
Hazard Indices ◽  
Local Data ◽  
Drought Impacts ◽  
Drought Hazard ◽  
Impact Data

&lt;p&gt;An increasing number of regions and countries are confronted with droughts as well as an increase in water demand. Inevitably, this leads to an increasing pressure on the available water resources and associated risks and economic impact for the water dependent sectors. In order to prevent big drought impacts, such as agricultural damage and food insecurity, timely and focused drought mitigation measures need to be carried out. To enable this, the detection of drought and its sector-specific risks at early stages needs to be improved. One of the main challenges is to develop compound and impact-oriented drought indices, that make optimal use of innovative techniques, satellite products, local data and other big data sets.&lt;/p&gt;&lt;p&gt;Here, we present the development of a Next Generation Drought Index (NGDI) that combines multiple freely available global data sources (eg. ERA5, MODIS, PCR-GLOBWB) to calculate a range of relevant drought hazard indices related to meteorological, hydrological, soil moisture and agricultural drought (eg. SPI, SPEI, SRI, SGI, VCI). The drought hazard indices are aggregated at district level, while considering the percentage area exposure of the drought impacted sector (exposure). In addition, the indices are enriched with local and national scale drought impact information (eg. online news items, social media data, EM-DAT database, GDO Drought news, national drought reports). Results are presented at sub-national scales in interactive spatial and temporal views, showing the combined drought indices and impact data.&lt;/p&gt;&lt;p&gt;The NGDI approach is being tested for the agricultural sector in Mali, a country with a vulnerable population and economy that faces frequent dry spells which heavily impact the functioning of the important agricultural activities that sustain a large part of the population. The computed drought indices are compared with local drought data and an analysis is made of the cross-correlations between the indices within the NGDI and collected impact data.&lt;/p&gt;&lt;p&gt;We aim at providing the NGDI information to a broad audience as well as co-creation of further NGDI developments. Hence, we would like to reach out to interested parties and identify collaboration opportunities.&lt;/p&gt;

scholarly journals Using integrated meteorological and hydrological indices to assess drought characteristics in southern Taiwan

2019 ◽  
Vol 50 (3) ◽  
pp. 901-914 ◽  
Author(s):  
Hsin-Fu Yeh
Keyword(s):  
River Basin ◽  
Drought Index ◽  
Standardized Precipitation Index ◽  
Assessment Method ◽  
Drought Indices ◽  
Trend Test ◽  
Integrated Analysis ◽  
Drought Assessment ◽  
Southern Taiwan ◽  
The Standardized Precipitation Index

Abstract Numerous drought index assessment methods have been developed to investigate droughts. This study proposes a more comprehensive assessment method integrating two drought indices. The Standardized Precipitation Index (SPI) and the Streamflow Drought Index (SDI) are employed to establish an integrated drought assessment method to study the trends and characteristics of droughts in southern Taiwan. The overall SPI and SDI values and the spatial and temporal distributions of droughts within a given year (November to October) revealed consistent general trends. Major droughts occurred in the periods of 1979–1980, 1992–1993, 1994–1995, and 2001–2003. According to the results of the Mann–Kendall trend test and the Theil–Sen estimator analysis, the streamflow data from the Sandimen gauging station in the Ailiao River Basin showed a 30% decrease, suggesting increasing aridity between 1964 and 2003. Hence, in terms of water resources management, special attention should be given to the Ailiao River Basin. The integrated analysis showed different types of droughts occurring in different seasons, and the results are in good agreement with the climatic characteristics of southern Taiwan. This study suggests that droughts cannot be explained fully by the application of a single drought index. Integrated analysis using multiple indices is required.

scholarly journals Technical Note: Comparing and ranking soil drought indices performance over Europe, through remote-sensing of vegetation

2010 ◽  
Vol 14 (2) ◽  
pp. 271-277 ◽  
Author(s):  
E. Peled ◽  
E. Dutra ◽  
P. Viterbo ◽  
A. Angert
Keyword(s):  
Soil Moisture ◽  
Drought Index ◽  
Technical Note ◽  
Temperate Climate ◽  
Drought Indices ◽  
Soil Drought ◽  
The Past ◽  
Analysis Technique ◽  
Global Soil ◽  
Warm Temperate

Abstract. In the past years there have been many attempts to produce and improve global soil-moisture datasets and drought indices. However, comparing and validating these various datasets is not straightforward. Here, interannual variations in drought indices are compared to interannual changes in vegetation, as captured by NDVI. By comparing the correlations of the different indices with NDVI we evaluated which drought index describes most realistically the actual changes in vegetation. Strong correlation between NDVI and the drought indices were found in areas that are classified as warm temperate climate with hot or warm dry summers. In these areas we ranked the PDSI, PSDI-SC, SPI3, and NSM indices, based on the interannual correlation with NDVI, and found that NSM outperformed the rest. Using this best performing index, and the ICA (Independent Component Analysis) technique, we analyzed the response of vegetation to temperature and soil-moisture stresses over Europe.

Drought

Geography ◽  
2020 ◽  
Author(s):  
Woonsup Choi
Keyword(s):  
Soil Moisture ◽  
Atmospheric Circulation ◽  
Agricultural Drought ◽  
Subsurface Water ◽  
Drought Indices ◽  
Human Society ◽  
Atmospheric Conditions ◽  
Spatial And Temporal Patterns ◽  
Circulation Anomalies ◽  
Atmospheric Circulation Anomalies

Drought is a natural disaster that has plagued human society throughout history. However, the meaning of drought varies by perspective and academic discipline, and the cause of drought is difficult to pinpoint. Despite the variation in its meaning, drought generally refers to the condition of an abnormally low amount of water for a given climate. Here the water can be precipitation, streamflow, soil moisture, groundwater, reservoir storage, and the like, but the lack of precipitation is a precursor for other types of drought. The lack of precipitation is often associated with anomalous atmospheric conditions such as atmospheric-circulation anomalies, higher-than-normal temperatures, and lower-than-normal relative humidity. Sea surface temperature anomalies may lead to sustained atmospheric-circulation anomalies. Drought defined as a lack of precipitation is often called meteorological or climatological drought. Other drought types can be classified within the context of the affected sectors, such as agricultural, hydrological, and socioeconomic drought. Agricultural drought generally refers to a lack of soil moisture, and hydrological drought refers to a lack of surface and subsurface water (e.g., streamflow and groundwater). Socioeconomic drought hampers human activities such as industry or water supply. As meteorological drought persists, other types of drought can follow. Such definitions of drought are regarded as conceptual definitions, but operational definitions are also necessary for quantitative understanding and management of drought events. Operational definitions use quantitative indices to identify the occurrence and characteristics of drought events such as onset, duration, termination, and deficit volume of drought. Much of existing drought research concerns developing, revising, and applying drought indices to investigate spatial and temporal patterns of drought at various geographical scales. Drought research has progressed along several directions, such as causes of drought, characteristics of drought events, impacts, and mitigation. Each of these directions is represented by the works cited in this article.

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