scholarly journals FORECASTING AND MONITORING AGRICULTURAL DROUGHT IN THE PHILIPPINES

2016 ◽  
Vol XLI-B8 ◽  
pp. 1263-1269 ◽  
Author(s):  
G. J. Perez ◽  
M. Macapagal ◽  
R. Olivares ◽  
E. M. Macapagal ◽  
J. C. Comiso
Keyword(s):  
Land Surface ◽  
Drought Index ◽  
Vegetation Index ◽  
The Philippines ◽  
Agricultural Drought ◽  
Stress Index ◽  
Drought Indices ◽  
Drought Event ◽  
Ancillary Data ◽  
Vulnerability Maps

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.

scholarly journals FORECASTING AND MONITORING AGRICULTURAL DROUGHT IN THE PHILIPPINES

2016 ◽  
Vol XLI-B8 ◽  
pp. 1263-1269
Author(s):  
G. J. Perez ◽  
M. Macapagal ◽  
R. Olivares ◽  
E. M. Macapagal ◽  
J. C. Comiso
Keyword(s):  
Land Surface ◽  
Drought Index ◽  
Vegetation Index ◽  
The Philippines ◽  
Agricultural Drought ◽  
Stress Index ◽  
Drought Indices ◽  
Drought Event ◽  
Ancillary Data ◽  
Vulnerability Maps

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.

scholarly journals Evaluation of Drought Indices Based on Thermal Remote Sensing of Evapotranspiration over the Continental United States

2011 ◽  
Vol 24 (8) ◽  
pp. 2025-2044 ◽  
Author(s):  
Martha C. Anderson ◽  
Christopher Hain ◽  
Brian Wardlow ◽  
Agustin Pimstein ◽  
John R. Mecikalski ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Surface ◽  
Drought Index ◽  
Temporal Correlation ◽  
Meteorological Drought ◽  
Rainfall Data ◽  
Added Value ◽  
Stress Index ◽  
Drought Indices ◽  
Shallow Water Table

Abstract The 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, they reflect only one component of the surface hydrologic cycle, and they cannot readily capture nonprecipitation-based moisture inputs to the land surface system (e.g., irrigation) that may temper drought impacts or variable rates of water consumption across a landscape. This study assesses the value of a new drought index based on remote sensing of evapotranspiration (ET). The evaporative stress index (ESI) quantifies anomalies in the ratio of actual to potential ET (PET), mapped using thermal band imagery from geostationary satellites. The study investigates the behavior and response time scales of the ESI through a retrospective comparison with the standardized precipitation indices and Palmer drought index suite, and with drought classifications recorded in the U.S. Drought Monitor for the 2000–09 growing seasons. Spatial and temporal correlation analyses suggest that the ESI performs similarly to short-term (up to 6 months) precipitation-based indices but can be produced at higher spatial resolution and without requiring any precipitation data. Unique behavior is observed in the ESI in regions where the evaporative flux is enhanced by moisture sources decoupled from local rainfall: for example, in areas of intense irrigation or shallow water table. Normalization by PET serves to isolate the ET signal component responding to soil moisture variability from variations due to the radiation load. This study suggests that the ESI is a useful complement to the current suite of drought indicators, with particular added value in parts of the world where rainfall data are sparse or unreliable.

scholarly journals Agricultural Drought Assessment in East Asia Using Satellite-Based Indices

2020 ◽  
Vol 12 (3) ◽  
pp. 444 ◽  
Author(s):  
Dong-Hyun Yoon ◽  
Won-Ho Nam ◽  
Hee-Jin Lee ◽  
Eun-Mi Hong ◽  
Song Feng ◽  
...  
Keyword(s):  
International Development ◽  
Land Surface ◽  
Joint Venture ◽  
The United States ◽  
Agricultural Drought ◽  
Stress Index ◽  
Drought Indices ◽  
Area Index ◽  
Drought Assessment ◽  
Wide Range

Drought is the meteorological phenomenon with the greatest impact on agriculture. Accordingly, drought forecasting is vital in lessening its associated negative impacts. Utilizing remote exploration in the agricultural sector allows for the collection of large amounts of quantitative data across a wide range of areas. In this study, we confirmed the applicability of drought assessment using the evaporative stress index (ESI) in major East Asian countries. The ESI is an indicator of agricultural drought that describes anomalies in actual/reference evapotranspiration (ET) ratios that are retrieved using remotely sensed inputs of land surface temperature (LST) and leaf area index (LAI). The ESI is available through SERVIR Global, a joint venture between the National Aeronautics and Space Administration (NASA) and the United States Agency for International Development (USAID). This study evaluated the performance of ESI in assessing drought events in South Korea. The evaluation of ESI is possible because of the availability of good statistical data. Comparing drought trends identified by ESI data from this study to actual drought conditions showed similar trends. Additionally, ESI reacted to the drought more quickly and with greater sensitivity than other drought indices. Our results confirmed that the ESI is advantageous for short and medium-term drought assessment compared to vegetation indices alone.

scholarly journals Assessing Spatiotemporal Drought Dynamics and Its Related Environmental Issues in the Mekong River Delta

2019 ◽  
Vol 11 (23) ◽  
pp. 2742 ◽  
Author(s):  
Tran ◽  
Tran ◽  
Myint ◽  
Latorre-Carmona ◽  
Ho ◽  
...  
Keyword(s):  
Time Series ◽  
Land Surface ◽  
Drought Index ◽  
Negative Impact ◽  
Statistical Significance ◽  
Standardized Precipitation Index ◽  
Agricultural Drought ◽  
Series Data ◽  
Drought Indices ◽  
Drought Severity

Drought is a major natural disaster that creates a negative impact on socio-economic development and environment. Drought indices are typically applied to characterize drought events in a meaningful way. This study aims at examining variations in agricultural drought severity based on the relationship between standardized ratio of actual and potential evapotranspiration (ET and PET), enhanced vegetation index (EVI), and land surface temperature (LST) derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) platform. A new drought index, called the enhanced drought severity index (EDSI), was developed by applying spatiotemporal regression methods and time-series biophysical data derived from remote sensing. In addition, time-series trend analysis in the 2001–2018 period, along with the Mann–Kendal (MK) significance test and the Theil Sen (TS) slope, were used to examine the spatiotemporal dynamics of environmental parameters (i.e., LST, EVI, ET, and PET), and geographically weighted regression (GWR) was subsequently applied in order to analyze the local correlations among them. Results showed that a significant correlation was discovered among LST, EVI, ET, and PET, as well as their standardized ratios (|r| > 0.8, p < 0.01). Additionally, a high performance of the new developed drought index, showing a strong correlation between EDSI and meteorological drought indices (i.e., standardized precipitation index (SPI) or the reconnaissance drought index (RDI)), measured at meteorological stations, giving r > 0.7 and a statistical significance p < 0.01. Besides, it was found that the temporal tendency of this phenomenon was the increase in intensity of drought, and that coastal areas in the study area were more vulnerable to this phenomenon. This study demonstrates the effectiveness of EDSI and the potential application of integrating spatial regression and time-series data for assessing regional drought conditions.

scholarly journals Development of Integrated Crop Drought Index by Combining Rainfall, Land Surface Temperature, Evapotranspiration, Soil Moisture, and Vegetation Index for Agricultural Drought Monitoring

2021 ◽  
Vol 13 (9) ◽  
pp. 1778
Author(s):  
Soo-Jin Lee ◽  
Nari Kim ◽  
Yangwon Lee
Keyword(s):  
Soil Moisture ◽  
Surface Temperature ◽  
Crop Yield ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Drought Index ◽  
Vegetation Index ◽  
The State ◽  
Agricultural Drought ◽  
Drought Monitoring

Various drought indices have been used for agricultural drought monitoring, such as Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI), Palmer Drought Severity Index (PDSI), Soil Water Deficit Index (SWDI), Normalized Difference Vegetation Index (NDVI), Vegetation Health Index (VHI), Vegetation Drought Response Index (VegDRI), and Scaled Drought Condition Index (SDCI). They incorporate such factors as rainfall, land surface temperature (LST), potential evapotranspiration (PET), soil moisture content (SM), and vegetation index to express the meteorological and agricultural aspects of drought. However, these five factors should be combined more comprehensively and reasonably to explain better the dryness/wetness of land surface and the association with crop yield. This study aims to develop the Integrated Crop Drought Index (ICDI) by combining the weather factors (rainfall and LST), hydrological factors (PET and SM), and a vegetation factor (enhanced vegetation index (EVI)) to better express the wet/dry state of land surface and healthy/unhealthy state of vegetation together. The study area was the State of Illinois, a key region of the U.S. Corn Belt, and the quantification and analysis of the droughts were conducted on a county scale for 2004–2019. The performance of the ICDI was evaluated through the comparisons with SDCI and VegDRI, which are the representative drought index in terms of the composite of the dryness and vegetation elements. The ICDI properly expressed both the dry and wet trend of the land surface and described the state of the agricultural drought accompanied by yield damage. The ICDI had higher positive correlations with the corn yields than SDCI and VegDRI during the crucial growth period from June to August for 2004–2019, which means that the ICDI could reflect the agricultural drought well in terms of the dryness/wetness of land surface and the association with crop yield. Future work should examine the other factors for ICDI, such as locality, crop type, and the anthropogenic impacts, on drought. It is expected that the ICDI can be a viable option for agricultural drought monitoring and yield management.

Development of satellite-based Surface water stress index considering surface water balance

2020 ◽  
Author(s):  
Ye-Seul Yun ◽  
Yang-Won Lee
Keyword(s):  
Surface Water ◽  
Water Balance ◽  
Drought Index ◽  
Supply And Demand ◽  
Agricultural Drought ◽  
Stress Index ◽  
Drought Indices ◽  
Water Shortages ◽  
Water Stress Index ◽  
The Impact

&lt;p&gt;The IPCC presented accelerated climate change and an increase in abnormal climate phenomena in the 21st century. This abnormal climate increases the frequency and intensity of extreme precipitation, resulting in changes in the water balance, such as precipitation and evaporation. Droughts are caused by prolonged water shortages, and it usually occurs in areas with subaverage rainfall. Drought is difficult to point precisely at the start and end, so its monitoring and forecasting are important to prepare for damage and mitigate impact. And although various satellite-based drought indices are being developed and used, it is still difficult to define drought quantitatively and to select a drought index suitable for the local situation. Currently, the drought indices used in Republic of Korea include SPI, which deals only with the water supply, and SPEI using the simple difference between precipitation and evapotranspiration. However, no standardized system of drought monitoring suitable for agricultural drought situations, such as the supply, consumption and impact of vegetation, has been established. However, it does not have a standardized system for monitoring drought agricultural drought suitable for situations such as the supply and demand of water and the impact on vegetation. this study tried to shows a new drought index that best expresses the drought in Korean cropland using long-term satellite data.&lt;/p&gt;

scholarly journals Remote Sensing Indices for Spatial Monitoring of Agricultural Drought in South Asian Countries

2021 ◽  
Vol 13 (11) ◽  
pp. 2059
Author(s):  
Muhammad Shahzaman ◽  
Weijun Zhu ◽  
Muhammad Bilal ◽  
Birhanu Asmerom Habtemicheal ◽  
Farhan Mustafa ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Vegetation Index ◽  
Vegetation Indices ◽  
Remote Sensing Data ◽  
Agricultural Drought ◽  
Stress Index ◽  
Drought Indices ◽  
Drought Period ◽  
Drought Assessment ◽  
The North

Drought is an intricate atmospheric phenomenon with the greatest impacts on food security and agriculture in South Asia. Timely and appropriate forecasting of drought is vital in reducing its negative impacts. This study intended to explore the performance of the evaporative stress index (ESI), vegetation health index (VHI), enhanced vegetation index (EVI), and standardized anomaly index (SAI) based on satellite remote sensing data from 2002–2019 for agricultural drought assessment in Afghanistan, Pakistan, India, and Bangladesh. The spatial maps were generated against each index, which indicated a severe agricultural drought during the year 2002, compared to the other years. The results showed that the southeast region of Pakistan, and the north, northwest, and southwest regions of India and Afghanistan were significantly affected by drought. However, Bangladesh faced substantial drought in the northeast and northwest regions during the drought year (2002). The longest drought period of seven months was observed in India followed by Pakistan and Afghanistan with six months, while, only three months were perceived in Bangladesh. The correlation between drought indices and climate variables such as soil moisture has remained a significant drought-initiating variable. Furthermore, this study confirmed that the evaporative stress index (ESI) is a good agricultural drought indicator, being quick and with greater sensitivity, and thus advantageous compared to the VHI, EVI, and SAI vegetation indices.

scholarly journals Spatial Evaluation of Droughts Using Selected Satellite-based Indices in the Upper Tana River Watershed, Kenya

2019 ◽  
pp. 1-13
Author(s):  
Harriette A. Okal ◽  
Felix K. Ngetich ◽  
Jeremiah M. Okeyo
Keyword(s):  
Drought Index ◽  
Vegetation Index ◽  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Agricultural Drought ◽  
Drought Indices ◽  
River Watershed ◽  
Noaa Avhrr ◽  
Tana River ◽  
Raster Maps

Aims: To identify the most appropriate drought indices for the identification and monitoring of historical meteorological and agricultural drought incidences and to explore the spatial characteristics of these droughts. Study design: GIS-based empirical research design. Place and Duration of Study: Upper Tana River Watershed, Kenya drought analysis covering a period of 1981 to 2013. Methodology: National Oceanic and Atmospheric Administration-Advanced Very High Resolution Radiometer (NOAA-AVHRR) provided raster maps for Normalized Difference Vegetation Index (NDVI) agricultural drought index, while GeoClim databased through Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) was used for retrieval of raster maps for Standardized Precipitation Index (SPI) meteorological drought index. ArcGIS version 10.3.1 facilitated image enhancement and correction for better visualization and interpretation. Results: Agricultural drought years were in 1983, 1987, 1993, 1996, 2000, 2004, 2005, 2008, and 2009 while meteorological drought years were in 1983, 1984, 1992, 1996, 1999, 2002, 2003, and 2011. Conclusion: Meteorological drought triggered events of agricultural drought. Both droughts showed a widespread pattern and were found to manifest at relatively same intervals during the study period.

scholarly journals Global downscaling of remotely sensed soil moisture using neural networks

2018 ◽  
Vol 22 (10) ◽  
pp. 5341-5356 ◽  
Author(s):  
Seyed Hamed Alemohammad ◽  
Jana Kolassa ◽  
Catherine Prigent ◽  
Filipe Aires ◽  
Pierre Gentine
Keyword(s):  
Soil Moisture ◽  
Spatial Resolution ◽  
Land Surface ◽  
Vegetation Index ◽  
Spatial Scales ◽  
Ancillary Data ◽  
Repeat Time ◽  
Spatiotemporal Scales ◽  
Better Than

Abstract. Characterizing soil moisture at spatiotemporal scales relevant to land surface processes (i.e., of the order of 1 km) is necessary in order to quantify its role in regional feedbacks between the land surface and the atmospheric boundary layer. Moreover, several applications such as agricultural management can benefit from soil moisture information at fine spatial scales. Soil moisture estimates from current satellite missions have a reasonably good temporal revisit over the globe (2–3-day repeat time); however, their finest spatial resolution is 9 km. NASA's Soil Moisture Active Passive (SMAP) satellite has estimated soil moisture at two different spatial scales of 36 and 9 km since April 2015. In this study, we develop a neural-network-based downscaling algorithm using SMAP observations and disaggregate soil moisture to 2.25 km spatial resolution. Our approach uses the mean monthly Normalized Differenced Vegetation Index (NDVI) as ancillary data to quantify the subpixel heterogeneity of soil moisture. Evaluation of the downscaled soil moisture estimates against in situ observations shows that their accuracy is better than or equal to the SMAP 9 km soil moisture estimates.

A novel index for ecological drought monitoring based on ecological water deficit: a case study of Northwestern China

2021 ◽  
Author(s):  
Tianliang Jiang ◽  
Xiaoling Su
Keyword(s):  
Water Deficit ◽  
Time Scales ◽  
Drought Index ◽  
Vegetation Index ◽  
Standardized Precipitation Index ◽  
Northwestern China ◽  
Drought Monitoring ◽  
Drought Indices ◽  
Drought Severity ◽  
Different Time Scales

&lt;p&gt;Although the concept of ecological drought was first defined by the Science for Nature and People Partnership (SNAPP) in 2016, there remains no widely accepted drought index for monitoring ecological drought. Therefore, this study constructed a new ecological drought monitoring index, the standardized ecological water deficit index (SEWDI). The SEWDI is based on the difference between ecological water requirements and consumption, referred to as the standardized precipitation index (SPI) method, which was used to monitor ecological drought in Northwestern China (NWRC). The performances of the SEWDI and four widely-used drought indices [standardized root soil moisture index (SSI), self-calibrated Palmer drought index (scPDSI), standardized precipitation-evaporation drought index (SPEI), and SPI) in monitoring ecological drought were evaluated through comparing the Pearson correlations between these indices and the standardized normalized difference vegetation index (SNDVI) under different time scales, wetness, and water use efficiencies (WUEs) of vegetation. Finally, the rotational empirical orthogonal function (REOF) was used to decompose the SEWDI at a 12-month scale in the NWRC during 1982&amp;#8211;2015 to obtain five ecological drought regions. The characteristics of ecological drought in the NWRC, including intensity, duration, and frequency, were extracted using run theory. The results showed that the performance of the SEWDI in monitoring ecological drought was highest among the commonly-used drought indices evaluated under different time scales [average correlation coefficient values (r) between SNDVI and drought indices: SEWDI&lt;sub&gt;&lt;/sub&gt;= 0.34, SSI&lt;sub&gt;&lt;/sub&gt;= 0.24, scPDSI&lt;sub&gt;&lt;/sub&gt;= 0.23, SPI&lt;sub&gt;&lt;/sub&gt;= 0.20, SPEI&lt;sub&gt;&lt;/sub&gt;= 0.18), and the 12-month-scale SEWDI was largely unaffected by wetness and WUE. In addition, the results of the monitoring indicated that serious ecological droughts in the NWRC mainly occurred in 1982&amp;#8211;1986, 1990&amp;#8211;1996, and 2005&amp;#8211;2010, primarily in regions I, II, and V, regions II, and IV, and in region III, IV, and V, respectively. This study provides a robust approach for quantifying ecological drought severity across natural vegetation areas and scientific evidence for governmental decision makers.&lt;/p&gt;

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