scholarly journals Unraveling the Relationship Between Tropical Storms and Agricultural Drought

2021 ◽  
Author(s):  
J. Y. Song ◽  
P. Abbaszadeh ◽  
P. Deb ◽  
H. Moradkhani
Keyword(s):  
Agricultural Drought ◽  
Tropical Storms ◽  
The Relationship

scholarly journals Estimating Sahelian and East African soil moisture using the Normalized Difference Vegetation Index

2013 ◽  
Vol 10 (6) ◽  
pp. 7963-7997 ◽  
Author(s):  
A. McNally ◽  
C. Funk ◽  
G. J. Husak ◽  
J. Michaelsen ◽  
B. Cappelaere ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Early Warning ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Agricultural Drought ◽  
Sub Saharan Africa ◽  
Sub Saharan ◽  
The Relationship ◽  
African Sahel

Abstract. Rainfall gauge networks in Sub-Saharan Africa are inadequate for assessing Sahelian agricultural drought, hence satellite-based estimates of precipitation and vegetation indices such as the Normalized Difference Vegetation Index (NDVI) provide the main source of information for early warning systems. While it is common practice to translate precipitation into estimates of soil moisture, it is difficult to quantitatively compare precipitation and soil moisture estimates with variations in NDVI. In the context of agricultural drought early warning, this study quantitatively compares rainfall, soil moisture and NDVI using a simple statistical model to translate NDVI values into estimates of soil moisture. The model was calibrated using in-situ soil moisture observations from southwest Niger, and then used to estimate root zone soil moisture across the African Sahel from 2001–2012. We then used these NDVI-soil moisture estimates (NSM) to quantify agricultural drought, and compared our results with a precipitation-based estimate of soil moisture (the Antecedent Precipitation Index, API), calibrated to the same in-situ soil moisture observations. We also used in-situ soil moisture observations in Mali and Kenya to assess performance in other water-limited locations in sub Saharan Africa. The separate estimates of soil moisture were highly correlated across the semi-arid, West and Central African Sahel, where annual rainfall exhibits a uni-modal regime. We also found that seasonal API and NDVI-soil moisture showed high rank correlation with a crop water balance model, capturing known agricultural drought years in Niger, indicating that this new estimate of soil moisture can contribute to operational drought monitoring. In-situ soil moisture observations from Kenya highlighted how the rainfall-driven API needs to be recalibrated in locations with multiple rainy seasons (e.g., Ethiopia, Kenya, and Somalia). Our soil moisture estimates from NDVI, on the other hand, performed well in Niger, Mali and Kenya. This suggests that the NDVI-soil moisture relationship may be more robust across rainfall regimes than the API because the relationship between NDVI and plant available water is less reliant on local characteristics (e.g., infiltration, runoff, evaporation) than the relationship between rainfall and soil moisture.

scholarly journals Weather-Related Hazards and Population Change

2016 ◽  
Vol 669 (1) ◽  
pp. 146-167 ◽  
Author(s):  
Elizabeth Fussell ◽  
Sara R. Curran ◽  
Matthew D. Dunbar ◽  
Michael A. Babb ◽  
Luanne Thompson ◽  
...  
Keyword(s):  
Population Growth ◽  
Population Change ◽  
Tropical Storms ◽  
Low Density ◽  
Weather Events ◽  
Declining Populations ◽  
The Relationship ◽  
Past Population ◽  
Future Population ◽  
Future Population Growth

Environmental determinists predict that people move away from places experiencing frequent weather hazards, yet some of these areas have rapidly growing populations. This analysis examines the relationship between weather events and population change in all U.S. counties that experienced hurricanes and tropical storms between 1980 and 2012. Our database allows for more generalizable conclusions by accounting for heterogeneity in current and past hurricane events and losses and past population trends. We find that hurricanes and tropical storms affect future population growth only in counties with growing, high-density populations, which are only 2 percent of all counties. In those counties, current year hurricane events and related losses suppress future population growth, although cumulative hurricane-related losses actually elevate population growth. Low-density counties and counties with stable or declining populations experience no effect of these weather events. Our analysis provides a methodologically informed explanation for contradictory findings in prior studies.

scholarly journals Comparison of Meteorological- and Agriculture-Related Drought Indicators across Ethiopia

Water ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 2218 ◽  
Author(s):  
Dawit Teweldebirhan Tsige ◽  
Venkatesh Uddameri ◽  
Farhang. Forghanparast ◽  
Elma Annette. Hernandez ◽  
Stephen. Ekwaro-Osire
Keyword(s):  
Soil Moisture ◽  
Meteorological Drought ◽  
Evaluation Framework ◽  
Agricultural Drought ◽  
Hydrologic Processes ◽  
Preparedness Planning ◽  
Drought Indicators ◽  
Drought Preparedness ◽  
The Relationship ◽  
Meteorological Droughts

Meteorological drought indicators are commonly used for agricultural drought contingency planning in Ethiopia. Agricultural droughts arise due to soil moisture deficits. While these deficits may be caused by meteorological droughts, the timing and duration of agricultural droughts need not coincide with the onset of meteorological droughts due to soil moisture buffering. Similarly, agricultural droughts can persist, even after the cessation of meteorological droughts, due to delayed hydrologic processes. Understanding the relationship between meteorological and agricultural droughts is therefore crucial. An evaluation framework was developed to compare meteorological- and agriculture-related drought indicators using a suite of exploratory and confirmatory tools. Receiver operator characteristics (ROC) was used to understand the covariation of meteorological and agricultural droughts. Comparisons were carried out between SPI-2, SPEI-2, and Palmer Z-index to assess intraseasonal droughts, and between SPI-6, SPEI-6, and PDSI for full-season evaluations. SPI was seen to correlate well with selected agriculture-related drought indicators, but did not explain all the variability noted in them. The correlation between meteorological and agricultural droughts exhibited spatial variability which varied across indicators. SPI is better suited to predict non-agricultural drought states than agricultural drought states. Differences between agricultural and meteorological droughts must be accounted for in order to devise better drought-preparedness planning.

scholarly journals Soil Moisture–Vegetation–Carbon Flux Relationship under Agricultural Drought Condition using Optical Multispectral Sensor

2020 ◽  
Vol 12 (9) ◽  
pp. 1359
Author(s):  
Chanyang Sur ◽  
Do-Hyuk Kang ◽  
Kyoung Jae Lim ◽  
Jae E. Yang ◽  
Yongchul Shin ◽  
...  
Keyword(s):  
Soil Moisture ◽  
South Korea ◽  
Land Surface ◽  
Time Lag ◽  
Co2 Flux ◽  
Agricultural Drought ◽  
Drought Period ◽  
Flux Tower ◽  
Vegetation Activity ◽  
The Relationship

Agricultural drought is triggered by a depletion of moisture content in the soil, which hinders photosynthesis and thus increases carbon dioxide (CO2) concentrations in the atmosphere. The aim of this study is to analyze the relationship between soil moisture (SM) and vegetation activity toward quantifying CO2 concentration in the atmosphere. To this end, the MODerate resolution imaging spectroradiometer (MODIS), an optical multispectral sensor, was used to evaluate two regions in South Korea for validation. Vegetation activity was analyzed through MOD13A1 vegetation indices products, and MODIS gross primary productivity (GPP) product was used to calculate the CO2 flux based on its relationship with respiration. In the case of SM, it was calculated through the method of applying apparent thermal inertia (ATI) in combination with land surface temperature and albedo. To validate the SM and CO2 flux, flux tower data was used which are the observed measurement values for the extreme drought period of 2014 and 2015 in South Korea. These two variables were analyzed for temporal variation on flux tower data as daily time scale, and the relationship with vegetation index (VI) was synthesized and analyzed on a monthly scale. The highest correlation between SM and VI (correlation coefficient (r) = 0.82) was observed at a time lag of one month, and that between VI and CO2 (r = 0.81) at half month. This regional study suggests a potential capability of MODIS-based SM, VI, and CO2 flux, which can be applied to an assessment of the global view of the agricultural drought by using available satellite remote sensing products.

scholarly journals Agricultural drought and spring barley yields in the Czech Republic

2008 ◽  
Vol 53 (No. 7) ◽  
pp. 306-316 ◽  
Author(s):  
M. Trnka ◽  
P. Hlavinka ◽  
D. Semerádová ◽  
M. Dubrovský ◽  
Z. Žalud ◽  
...  
Keyword(s):  
Czech Republic ◽  
Data Analysis ◽  
Spring Barley ◽  
Meteorological Drought ◽  
The Other ◽  
Agricultural Drought ◽  
Threshold Values ◽  
The Czech Republic ◽  
Southern Moravia ◽  
The Relationship

The relationship between detrended district yields of spring barley (1961&minus;2000) and meteorological drought was assessed by Palmer Z-index. We found that the seasonal water balance (April&minus;June) significantly (<i>P</i> = 0.05) influences the spring barley production in 51 out of 62 evaluated districts. Coefficients of correlation varied in individual districts from 0.19 to 0.70, with the highest values being found in southern Moravia. Data analysis revealed the presence of six distinct groups of districts with a specific drought-yield relationship. The most drought-sensitive cluster included five districts in the South East of the country. On the other hand, the districts in Northern Moravia and Silesia belong among the least sensitive to agricultural drought. The study also defined threshold values of seasonal drought (sums of relative Palmer Z-index lower than &minus;8 and &minus;10, respectively), below which medium to severe spring barley yield reductions are very likely, regardless of the district of occurrence.

scholarly journals Impact of Agricultural Drought on Sunflower Production across Hungary

Atmosphere ◽  
2021 ◽  
Vol 12 (10) ◽  
pp. 1339
Author(s):  
Endre Harsányi ◽  
Bashar Bashir ◽  
Firas Alsilibe ◽  
Karam Alsafadi ◽  
Abdullah Alsalman ◽  
...  
Keyword(s):  
Climate Change ◽  
Crop Production ◽  
Regional Scale ◽  
Standardized Precipitation Index ◽  
Agricultural Drought ◽  
Positive Trend ◽  
The Standardized Precipitation Index ◽  
The Impact ◽  
The Relationship ◽  
Sunflower Production

In the last few decades, agricultural drought (Ag.D) has seriously affected crop production and food security worldwide. In Hungary, little research has been carried out to assess the impacts of climate change, particularly regarding droughts and crop production, and especially on regional scales. Thus, the main aim of this study was to evaluate the impact of agricultural drought on sunflower production across Hungary. Drought data for the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI) were collected from the CARBATCLIM database (1961–2010), whereas sunflower production was collected from the Hungarian national statistical center (KSH) on regional and national scales. To address the impact of Ag.D on sunflower production, the sequence of standardized yield residuals (SSYR) and yield losses YlossAD was applied. Additionally, sunflower resilience to Ag.D (SRAg.D) was assessed on a regional scale. The results showed that Ag.D is more severe in the western regions of Hungary, with a significantly positive trend. Interestingly, drought events were more frequent between 1990 and 2010. Moreover, the lowest SSYR values were reported as −3.20 in the Hajdu-Bihar region (2010). In this sense, during the sunflower growing cycle, the relationship between SSYR and Ag.D revealed that the highest correlations were recorded in the central and western regions of Hungary. However, 75% of the regions showed that the plantation of sunflower is not resilient to drought where SRAg.Dx < 1. To cope with climate change in Hungary, an urgent mitigation plan should be implemented.

scholarly journals Shipwrecks on Roncador Cay, the Caribbean Sea and Their Relationship with Hurricanes, 1492-1920

2021 ◽  
Author(s):  
William Gomez Pretel ◽  
Moon-Soo Jeong
Keyword(s):  
Environmental Conditions ◽  
Caribbean Sea ◽  
Future Research ◽  
Tropical Storms ◽  
Underwater Cultural Heritage ◽  
Search Results ◽  
New Information ◽  
Western Caribbean ◽  
The Caribbean ◽  
The Relationship

AbstractPrevious studies suggest that tropical storms and hurricanes are among the leading causes of shipwrecks in the Caribbean Sea since 1492. This paper will explore the relationship between shipwrecks and hurricanes in the Western Caribbean, particularly Roncador Cay, a place with complex environmental conditions that have made this area a trap for ships, but has up until now, been without rigorous shipwreck analysis. This study covers the period 1492 to 1920 with search results of 23 shipwrecks and 37 tropical cyclones compiled in databases, reviewing seven wrecks already documented and revealing new information on 16, previously not recorded. The sources provide detailed shipwrecks, demonstrating that most accidents occurred by unspecific causes and no direct relationship with hurricanes but were influenced by environmental conditions, such as geomorphology, cold fronts, or currents. There is also a reflection on the sociocultural changes and the influence of power in the region. The study includes a suggested tool for future research, protecting the wreck site and emphasizing the importance of the underwater cultural heritage as an indicator of the active maritime past.

Agricultural drought analyses for temperate Australia using a biophysical pasture model. 2. Relationship between rainfall and the start and end of predicted droughts

2008 ◽  
Vol 59 (11) ◽  
pp. 1061 ◽  
Author(s):  
G. M. Lodge ◽  
I. R. Johnson
Keyword(s):  
New South ◽  
Summer Rainfall ◽  
Growing Season ◽  
Agricultural Drought ◽  
Wagga Wagga ◽  
Climate Data ◽  
Winter Rainfall ◽  
Rainfall Occurrence ◽  
South Wales ◽  
The Relationship

This paper reports relationships between predicted soil water content (SWC) on the first day of the month (SWCFOM, mm of water) and previous monthly rainfall for 100 years of daily climate data (1905–2005) at four sites (Albany, Western Australia; Hamilton, Victoria; and Wagga Wagga and Barraba, New South Wales). Overall, predicted SWCFOM was correlated (P < 0.05) with rainfall in the previous one, two, or three months. However, the proportion of variation in SWCFOM that could be attributed to its regression on previous rainfall was variable and the relationship tended to improve when individual months were examined. At the three winter-rainfall sites (Albany, Hamilton, and Wagga Wagga), there was a reasonably good relationship between the start of a predicted drought and the end of the growing season and also between the end of a predicted drought and the occurrence of break-of-season. However, for the summer-rainfall dominant site at Barraba, rainfall occurrence was less seasonally defined and there was no clear relationship. While analysis of historical rainfall data for the months in which predicted agricultural droughts started or ended provided some useful insights, it was concluded that it would probably be more instructive to model SWC outcomes for a range of future rainfall scenarios and then examine their likelihood of occurrence using rainfall percentiles.

scholarly journals Impact of Soil Moisture Data Characteristics on the Sensitivity to Crop Yields Under Drought and Excess Moisture Conditions

2019 ◽  
Vol 11 (4) ◽  
pp. 372 ◽  
Author(s):  
Catherine Champagne ◽  
Jenelle White ◽  
Aaron Berg ◽  
Stephane Belair ◽  
Marco Carrera
Keyword(s):  
Soil Moisture ◽  
Surface Soil ◽  
Crop Yields ◽  
Agricultural Drought ◽  
Data Sets ◽  
Surface Soil Moisture ◽  
Short Baseline ◽  
Data Set ◽  
Soil Moisture Data ◽  
The Relationship

Soil moisture is often considered a direct way of quantifying agricultural drought since it is a measure of the availability of water to support crop growth. Measurements of soil moisture at regional scales have traditionally been sparse, but advances in land surface modelling and the development of satellite technology to indirectly measure surface soil moisture has led to the emergence of a number of national and global soil moisture data sets that can provide insight into the dynamics of agricultural drought. Droughts are often defined by normal conditions for a given time and place; as a result, data sets used to quantify drought need a representative baseline of conditions in order to accurately establish a normal. This presents a challenge when working with earth observation data sets which often have very short baselines for a single instrument. This study assessed three soil moisture data sets: a surface satellite soil moisture data set from the Soil Moisture and Ocean Salinity (SMOS) mission operating since 2010; a blended surface satellite soil moisture data set from the European Space Agency Climate Change Initiative (ESA-CCI) that has a long history and a surface and root zone soil moisture data set from the Canadian Meteorology Centre (CMC)’s Regional Deterministic Prediction System (RDPS). An iterative chi-squared statistical routine was used to evaluate each data set’s sensitivity to canola yields in Saskatchewan, Canada. The surface soil moisture from all three data sets showed a similar temporal trend related to crop yields, showing a negative impact on canola yields when soil moisture exceeded a threshold in May and June. The strength and timing of this relationship varied with the accuracy and statistical properties of the data set, with the SMOS data set showing the strongest relationship (peak X2 = 170 for Day of Year 145), followed by the ESA-CCI (peak X2 = 89 on Day of Year 129) and then the RDPS (peak X2 = 65 on Day of Year 129). Using short baseline soil moisture data sets can produce consistent results compared to using a longer data set, but the characteristics of the years used for the baseline are important. Soil moisture baselines of 18–20 years or more are needed to reliably estimate the relationship between high soil moisture and high yielding years. For the relationship between low soil moisture and low yielding years, a shorter baseline can be used, with reliable results obtained when 10–15 years of data are available, but with reasonably consistent results obtained with as few as 7 years of data. This suggests that the negative impacts of drought on agriculture may be reliably estimated with a relatively short baseline of data.

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