DROUGHT RISK ASSESSMENT DURING THE DRY SEASON IN TIEN RIVER ESTUARY

2020 ◽  
Vol 65 (6) ◽  
pp. 191-200
Author(s):  
Hung Dao Ngoc ◽  
Luan Nguyen Thanh
Keyword(s):  
Large Scale ◽  
Vegetation Index ◽  
Satellite Image ◽  
Standardized Precipitation Index ◽  
River Estuary ◽  
Meteorological Drought ◽  
Dry Season ◽  
Drought Risk ◽  
Widespread Application ◽  
Landsat Satellite

Drought simply is a period of moisture deficiency. It depends on temperature, evaporation capacity, vegetation cover, topography, etc., in addition, it often happens on a large scale making it difficult to use traditional research methods. With the development and widespread application of remote sensing technology and geographic information systems (GIS), the use of satellite images as well as GIS software is becoming more and more effective in monitoring, monitoring and assessing drought. In this study, the author assessed the risk of drought at Tien river estuary through two indices: Normalize Difference Vegetation Index (NDVI) and Standardized Precipitation Index (SPI) during the dry season months of 1991, 2001, 2010 and 2018. SPI values are interpolated to construct spatial modeling of meteorological drought levels. Through the LANDSAT satellite image, NDVI is calculated and built on a map of drought levels. Weighted overlay SPI and NDVI map layers for a drought risk map. Research results have shown that the Tien river estuary area is divided into 2 zones: light drought and moderate drought occurs in the dry season. Drought occurred with strong intensity in the eastern coastal area of Ben Tre and Tra Vinh provinces, the deeper the inland the level of drought decreased.

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

2015 ◽  
Vol XL-7/W3 ◽  
pp. 337-344 ◽  
Author(s):  
B. Brede ◽  
J. Verbesselt ◽  
L. Dutrieux ◽  
M. Herold
Keyword(s):  
Large Scale ◽  
Vegetation Index ◽  
Standardized Precipitation Index ◽  
Dry Season ◽  
Drought Indices ◽  
Amazon Forest ◽  
Enhanced Vegetation Index ◽  
Sun Sensor ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Sensor Geometry

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.

scholarly journals Ecosystem Drought Response Timescales from Thermal Emission versus Shortwave Remote Sensing

2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Erika Andujar ◽  
Nir Y. Krakauer ◽  
Chuixiang Yi ◽  
Felix Kogan
Keyword(s):  
Remote Sensing ◽  
Large Scale ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Thermal Emission ◽  
Plant Stress ◽  
Meteorological Drought ◽  
Condition Index ◽  
Vegetation Health ◽  
Vegetation Health Index

Remote sensing is used for monitoring the impacts of meteorological drought on ecosystems, but few large-scale comparisons of the response timescale to drought of different vegetation remote sensing products are available. We correlated vegetation health products derived from polar-orbiting radiometer observations with a meteorological drought indicator available at different aggregation timescales, the Standardized Precipitation Evapotranspiration Index (SPEI), to evaluate responses averaged globally and over latitude and biome. The remote sensing products are Vegetation Condition Index (VCI), which uses normalized difference vegetation index (NDVI) to identify plant stress, Temperature Condition Index (TCI), based on thermal emission as a measure of surface temperature, and Vegetation Health Index (VHI), the average of VCI and TCI. Globally, TCI correlated best with 2-month timescale SPEI, VCI correlated best with longer timescale droughts (peak mean correlation at 13 months), and VHI correlated best at an intermediate timescale of 4 months. Our results suggest that thermal emission (TCI) may better detect incipient drought than vegetation color (VCI). VHI had the highest correlations with SPEI at aggregation times greater than 3 months and hence may be the most suitable product for monitoring the effects of long droughts.

scholarly journals Risk assessment of meteorological drought in China under RCP scenarios from 2016 to 2050

2016 ◽  
Author(s):  
Kuo Li ◽  
Jie Pan
Keyword(s):  
Climate Change ◽  
Risk Assessment ◽  
Water Resources ◽  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Mitigation Strategies ◽  
Sensitivity Index ◽  
Drought Risk ◽  
Emission Scenarios ◽  
The Impact

Abstract. Climate change has been a hotspot of scientific research in the world for decades, which caused serious effects of agriculture, water resources, ecosystem, environment, human health and so on. In China, drought accounts for almost 50 % of the total loss among all the meteorological disasters. In this article the interpolated and corrected precipitation of one GCM (HadGEM2-ES) output under four emission scenarios (RCP2.6, 4.5, 6.0, 8.5) were used to analyze the drought. The standardized precipitation index (SPI) calculated with these data was used to assess the climate change impact on droughts from meteorological perspectives. Based on five levels of SPI, an integrated index of drought hazard (IIDH) was established, which could explain the frequency and intensity of meteorological drought in different regions. According to yearbooks of different provinces, 15 factors have been chosen which could represent the impact of drought on human being, crops, water resources and economy. Exposure index, sensitivity index and adaptation index have been calculated in almost 2400 counties and vulnerability of drought has been evaluated. Based on hazard and vulnerability evaluation of drought, risk assessment of drought in China under the RCP2.6, 4.5, 6.0, 8.5 emission scenarios from 2016 to 2050 has been done. Results from such a comprehensive study over the whole country could be used not only to inform on potential impacts for specific sectors but also can be used to coordinate adaptation/mitigation strategies among different sectors/regions by the central government.

scholarly journals Finescale Evaluation of Drought in a Tropical Setting: Case Study in Sri Lanka

2009 ◽  
Vol 48 (1) ◽  
pp. 77-88 ◽  
Author(s):  
Bradfield Lyon ◽  
Lareef Zubair ◽  
Vidhura Ralapanawe ◽  
Zeenas Yahiya
Keyword(s):  
Sri Lanka ◽  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Drought Indices ◽  
Drought Risk ◽  
Mitigation And Adaptation ◽  
Wide Range ◽  
Drought Relief ◽  
Drought Indicators ◽  
The Standardized Precipitation Index

Abstract In regions of climatic heterogeneity, finescale assessment of drought risk is needed for policy making and drought management, mitigation, and adaptation. The relationship between drought relief payments (a proxy for drought risk) and meteorological drought indicators is examined through a retrospective analysis for Sri Lanka (1960–2000) based on records of district-level drought relief payments and a dense network of 284 rainfall stations. The standardized precipitation index and a percent-of-annual-average index for rainfall accumulated over 3, 6, 9, and 12 months were used, gridded to a spatial resolution of 10 km. An encouraging correspondence was identified between the spatial distribution of meteorological drought occurrence and historical drought relief payments at the district scale. Time series of drought indices averaged roughly over the four main climatic zones of Sri Lanka showed statistically significant (p < 0.01) relationships with the occurrence of drought relief. The 9-month cumulative drought index provided the strongest relationships overall, although 6- and 12-month indicators provided generally similar results. Some cases of appreciable drought without corresponding relief payments could be attributed to fiscal pressures, as during the 1970s. Statistically significant relationships between drought indicators and relief payments point to the potential utility of meteorological drought assessments for disaster risk management. In addition, the study provides an empirical approach to testing which meteorological drought indicators bear a statistically significant relationship to drought relief across a wide range of tropical climates.

scholarly journals Drought Risk Assessment in the Khushab Region of Pakistan Using Satellite Remote Sensing and Geospatial Methods

2019 ◽  
Vol 10 (1) ◽  
pp. 48-56 ◽  
Author(s):  
Muhammad Khubaib Abuzar ◽  
Muhammad Shafiq ◽  
Syed Amer Mahmood ◽  
Muhammad Irfan ◽  
Tayyaba Khalil ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Social Life ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Standardized Precipitation Index ◽  
Temporal Analysis ◽  
Agricultural Drought ◽  
Natural Phenomenon ◽  
Drought Risk ◽  
Gis And Remote Sensing

Drought is a harmful and slow natural phenomenon that has significant effects on the economy, social life,agriculture and environment of the country. Due to its slow process it is difficult to study this phenomenon. RemoteSensing and GIS tools play a key role in studying different hazards like droughts. The main objective of the study wasto investigate drought risk by using GIS and Remote Sensing techniques in district Khushab, Pakistan. Landsat ETMimages for the year 2003, 2009 and 2015 were utilized for spatial and temporal analysis of agricultural andmeteorological drought. Normalized difference vegetation index (NDVI) Standardized Precipitation Index (SPI) andrainfall anomaly indices were calculated to identify the drought prone areas in the study area. To monitormeteorological drought SPI values were used and NDVI was calculated for agricultural drought. These indices wereintegrated to compute the spatial and temporal drought maps. Three zones; no drought, slight drought and moderatedrought were identified. Final drought map shows that 30.21% of the area faces moderate drought, 28.36% faces slightdrought while nearly 41.3% faces no drought situation. Drought prevalence and severity is present more in the southernpart of Khushab district than the northern part. Most of the northern part is not under any type of drought. Thus, anoverall outcome of this study shows that risk areas can be assessed appropriately by integration of various data sourcesand thereby management plans can be prepared to deal with the hazard.

scholarly journals Meteorological Drought Analysis and Return Periods over North and West Africa and Linkage with El Niño–Southern Oscillation (ENSO)

2021 ◽  
Vol 13 (23) ◽  
pp. 4730
Author(s):  
Malak Henchiri ◽  
Tertsea Igbawua ◽  
Tehseen Javed ◽  
Yun Bai ◽  
Sha Zhang ◽  
...  
Keyword(s):  
West Africa ◽  
Large Scale ◽  
Southern Oscillation ◽  
Standardized Precipitation Index ◽  
Joint Probability ◽  
Meteorological Drought ◽  
Socioeconomic Impacts ◽  
The North ◽  
The Standardized Precipitation Index ◽  
The North Atlantic Oscillation

Droughts are one of the world’s most destructive natural disasters. In large regions of Africa, droughts can have strong environmental and socioeconomic impacts. Understanding the mechanism that drives drought and predicting its variability is important for enhancing early warning and disaster risk management. Taking North and West Africa as the study area, this study adopted multi-source data and various statistical analysis methods, such as the joint probability density function (JPDF), to study the meteorological drought and return years across a long term (1982–2018). The standardized precipitation index (SPI) was used to evaluate the large-scale spatiotemporal drought characteristics at 1–12-month timescales. The intensity, severity, and duration of drought in the study area were evaluated using SPI–12. At the same time, the JPDF was used to determine the return year and identify the intensity, duration, and severity of drought. The Mann-Kendall method was used to test the trend of SPI and annual precipitation at 1–12-month timescales. The pattern of drought occurrence and its correlation with climate factors were analyzed. The results showed that the drought magnitude (DM) of the study area was the highest in 2008–2010, 2000–2003, and 1984–1987, with the values of 5.361, 2.792, and 2.187, respectively, and the drought lasting for three years in each of the three periods. At the same time, the lowest DM was found in 1997–1998, 1993–1994, and 1991–1992, with DM values of 0.113, 0.658, and 0.727, respectively, with a duration of one year each time. It was confirmed that the probability of return to drought was higher when the duration of drought was shorter, with short droughts occurring more regularly, but not all severe droughts hit after longer time intervals. Beyond this, we discovered a direct connection between drought and the North Atlantic Oscillation Index (NAOI) over Morocco, Algeria, and the sub-Saharan countries, and some slight indications that drought is linked with the Southern Oscillation Index (SOI) over Guinea, Ghana, Sierra Leone, Mali, Cote d’Ivoire, Burkina Faso, Niger, and Nigeria.

scholarly journals Cartographie De L’état Du Couvert Végétal Du Nord De La Côte D’ivoire À Partir D’images Satellites: Exemple De La Zone De Korhogo

2016 ◽  
Vol 12 (29) ◽  
pp. 204
Author(s):  
Avy StéphaneKoff ◽  
Abderrahman Ait Fora ◽  
Hicham Elbelrhiti
Keyword(s):  
Cote D'ivoire ◽  
Vegetation Cover ◽  
Vegetation Index ◽  
Côte D’Ivoire ◽  
Normalized Difference Vegetation Index ◽  
Satellite Image ◽  
The State ◽  
Cote D’Ivoire ◽  
Côte D'ivoire ◽  
Landsat Satellite

The purpose of this study is to determine the state of the vegetation cover in the region of Korhogo through remote sensing. Nowadays, the problem of desertification in the Sahel is serious. This could be explained by the phenomenon of climate change. We want to map the state of the vegetation cover in the study area. This study therefore focuses on the state of the vegetation cover in the region of Korhogo in northern Côte d’Ivoire. We will use one Landsat satellite image from December 16th 2000 and proceed with image processing. Processing techniques by the normalized difference vegetation index, the index armor and colorful composition 472. After these treatments in our pictures, we observe the behavior of vegetation. We can then get an overview of the vegetation in this area.

scholarly journals DETECTION OF ACID SLUDGE CONTAMINATED AREA BASED ON NORMALIZED DIFFERENCE VEGETATION INDEX (NDVI) VALUE

2017 ◽  
Vol 11 (1) ◽  
pp. 21
Author(s):  
Nanik Suryo Haryani ◽  
Sayidah Sulma ◽  
Junita Monika Pasaribu
Keyword(s):  
Satellite Images ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Remote Sensing Data ◽  
Dry Season ◽  
Wet Season ◽  
Multi Temporal ◽  
Acid Sludge ◽  
Landsat Satellite ◽  
Solid Form

The solid form of oil heavy metal waste is  known as acid sludge. The aim of this research is to exercise the correlation between acid sludge concentration in soil and NDVI value, and further studying the Normalized Difference Vegetation Index (NDVI) anomaly by multi-temporal Landsat satellite images. The implemented method is NDVI.  In this research, NDVI is analyzed using the  remote sensing data  on dry season and wet season.  Between 1997 to 2012, NDVI value in dry season  is around – 0.007 (July 2001) to 0.386 (May 1997), meanwhile in wet season  NDVI value is around – 0.005 (November 2006) to 0.381 (December 1995).  The high NDVI value shows the leaf health or  thickness, where the low NDVI indicates the vegetation stress and rareness which can be concluded as the evidence of contamination. The rehabilitation has been executed in the acid sludge contaminated location, where the high value of NDVI indicates the successfull land rehabilitation effort.

scholarly journals Pemetaan Indek Kekeringan dan Sebaran Titik Hotspot Daerah Potensi Kebakaran Hutan dan Lahan di Propinsi Riau

2018 ◽  
Vol 5 (1) ◽  
pp. 1
Author(s):  
Yotta Autika ◽  
Aras Mulyadi ◽  
Yusni Ikhwan Siregar
Keyword(s):  
Land Use ◽  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Dry Season ◽  
Wet Season ◽  
Index Method ◽  
Spi Index ◽  
Maximum Duration ◽  
Relationship Of ◽  
The Relationship

Riau is one of the most vulnerable provinces to forest and land fires in Indonesia. The potency for forest and land fires is inseparable from the presence of peatlands and exacerbated by drought. The purpose of this research is to know the characteristics of meteorological drought using SPI (Standardized Precipitation Index) method and its relation with forest and peatland fire as one of disaster management effort in Riau Province. The data used in this research are monthly rainfall data from meteorology station and rainfall posts of BMKG, hotspot data from NOAA satellite, map of Forest Use Agreement (TGHK), peat land map and land use map. Analysis of drought characteristics was done by calculating monthly SPI-1 then determining the maximum duration, intensity, severity and drought exposure. Determination of the severity of the drought by weighting and suspension method was based on duration and intensity while drought exposure was done by overlaying the map of the severity of the drought with the land use map. Meanwhile, to know the potential of forest and land fires began with the selection of hotspots on peatlands and forest areas every month then created a graph of the relationship of meteorological drought with the number of hotspots. Then, to see the relationship of drought distribution to the distribution of hotspots in dry season (MK) and wet season (MH) of 2015 was done by overlaying cover the drought distribution with hotspot distribution. The result shows that drought characteristic in the most of Riau province has maximum duration around 4-6 months, dry category of intensity, high category of severity with exposure area in paddy field, field, habitation, and plantation. Then, negative SPI Index (dry condition) has potential to increase the number of hotspots otherwise positive SPI index (wet condition) leads to low occurrence of hotspot. The drought distribution in the dry season (July, August, September) of 2015 triggers the number of hotspots during drought conditions, while in wet season (April, November, December) of 2015 are dominated by normal conditions, some areas are dry and wet, resulting in lower hotspots distribution compared to the dry season.

scholarly journals Monitoring agricultural drought using geospatial techniques: a case study of Thal region of Punjab, Pakistan

2020 ◽  
Vol 11 (S1) ◽  
pp. 203-216 ◽  
Author(s):  
Muhammad Amin ◽  
Mobushir Riaz Khan ◽  
Sher Shah Hassan ◽  
Aftab Ahmad Khan ◽  
Muhammad Imran ◽  
...  
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Wheat Yield ◽  
Standardized Precipitation Index ◽  
Weather Conditions ◽  
Agricultural Drought ◽  
Wheat Crop ◽  
Drought Risk ◽  
Risk Map ◽  
Agricultural Risk

Abstract The Thal region of Punjab often experiences dry weather conditions with extreme variability in rainfall on a spatiotemporal scale during Rabi cropping season. The current study assesses the impacts of agricultural drought on wheat crops for 2000–2015. MOD13Q1 and CHIRPS data were used for identifying and assessing variation in agricultural drought patterns and severity. Standardized Precipitation Index (SPI), Normalized Difference Vegetation Index (NDVI), Vegetation Condition Index (VCI), Stress Vegetation Index (STVI) and wheat crop yield anomalies were computed to characterize the gravity of drought across the Thal region. The results indicate that the wheat Rabi cropping seasons of the years 2000–2002 experienced extreme agricultural drought, with a spatial difference in severity level causing low and poor yield, while the years 2011 and 2014 were almost normal among all the years, leaving varied impacts on wheat yield. The combined agricultural risk map was generated by integrating the agricultural and meteorological droughts severity maps. The combined risk map generated using weighted overlay analysis of all the parameters indicate that the total Thal area can be classified into slight, moderate and no drought covering 28.12, 12.76, and 59.12% respectively of the total area. Hence an agricultural risk map would be extremely helpful as a tool to guide the decision-making process for monitoring drought risk on agricultural productivity.

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