A Non-Stationary Reconnaissance Drought Index (NRDI) for Drought Monitoring in a Changing Climate

Droughts are one of the primary natural disasters that affect agricultural economies, as well as the fire hazards of territories. Monitoring and researching droughts is of great importance for agricultural disaster prevention and reduction. The research significance of investigating the hysteresis of agricultural to meteorological droughts is to provide an important reference for agricultural drought monitoring and early warnings. Remote sensing drought monitoring indices can be employed for rapid and accurate drought monitoring at regional scales. In this paper, the Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indices and the surface temperature product are used as the data sources. Calculating the temperature vegetation drought index (TVDI) and constructing a comprehensive drought disaster index (CDDI) based on the crop growth period allowed drought conditions and spatiotemporal evolution patterns in the Volgograd region in 2010 and 2012 to be effectively monitored. The causes of the drought were then analyzed based on the sensitivity of a drought to meteorological factors in rain-fed and irrigated lands. Finally, the lag time of agricultural to meteorological droughts and the hysteresis in different growth periods were analyzed using statistical analyses. The research shows that (1) the main drought patterns in 2010 were spring droughts from April to May and summer droughts from June to August, and the primary drought patterns in 2012 were spring droughts from April to June, with an affected area that reached 3.33% during the growth period; (2) local drought conditions are dominated by the average surface temperature factor. Rain-fed lands are sensitive to the temperature and are therefore prone to summer droughts. Irrigated lands are more sensitive to water shortages in the spring and less sensitive to extremely high temperature conditions; (3) there is a certain lag between meteorological and agricultural droughts during the different growth stages. The strongest lag relationship was found in the planting stage and the weakest one was found in the dormancy stage. Therefore, the meteorological drought index in the growth period has a better predictive ability for agricultural droughts during the appropriately selected growth stages.

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Assessing the soil moisture drought index for agricultural drought monitoring based on green vegetation fraction retrieval methods

Natural Hazards ◽

10.1007/s11069-021-04693-x ◽

2021 ◽

Author(s):

Rongjun Wu ◽

Qi Li

Keyword(s):

Soil Moisture ◽

Drought Index ◽

Agricultural Drought ◽

Drought Monitoring ◽

Vegetation Fraction ◽

Green Vegetation

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On The Reduction of Inaccuracies in Drought Monitoring - A Novel Blended Procedure for Standardized Type Drought Indicators

10.21203/rs.3.rs-115294/v1 ◽

2020 ◽

Author(s):

Muhammad Khan ◽

He Jiang ◽

Zulfiqar Ali ◽

Amna Nazeer ◽

Guangheng Ni ◽

...

Keyword(s):

Water Management ◽

Drought Index ◽

Drought Monitoring ◽

Drought Indices ◽

Management Research ◽

Climatic Zones ◽

Data Mining Approach ◽

Gauge Station ◽

Pros And Cons ◽

Increasing Temperature

Abstract Due to climate change and an increasing temperature, drought is prevailing in several parts of the globe. Therefore, drought monitoring is a challenging task in hydrology and water management research. Drought is occurring recurrently in various climatic zones around the world. In literature, in that respect, there are several drought monitoring indicators. Regardless of their pros and cons, their abounded creates a chaotic scenario in analysis and reanalysis in certain gauge station. This research aims to improve drought monitoring system by providing a comprehensive data mining approach under principle component analysis. Consequently, we propose a new index named: Seasonal Mixture Standardized Drought Index (SMSDI). In our preliminary analysis, we have included three multiscaler Standardized Drought Indices (SDIs). In application, we have applied our proposed indicator on three meteorological gauge stations located in Pakistan. For comparative assessment, individual SDI has used to investigate the association and consistency with SMSDI. Results presented in the current study demonstrated that the SMSDI has significant correlation with individual SDIs. Hence, we conclude that the procedure of SMSDI can be deployed in hydrology and water management research for extracting reliable information related to future drought.

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

10.5194/egusphere-egu21-5439 ◽

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

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&#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= 0.34, SSI= 0.24, scPDSI= 0.23, SPI= 0.20, SPEI= 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&#8211;1986, 1990&#8211;1996, and 2005&#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.

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