{"title":"印度哥达瓦里盆地农业干旱特征的短期卫星土壤湿度","authors":"Hussain Palagiri, Manali Pal, Rajib Maity","doi":"10.1007/s10661-025-14044-z","DOIUrl":null,"url":null,"abstract":"<div><p>Soil moisture (SM) is crucial for identifying agricultural drought, but due to the limited availability of large scale and high-resolution SM data, drought indices based on hydro-meteorological variables are commonly used. Recent advancements in microwave remote sensing, such as the Soil Moisture Active Passive (SMAP) satellite, provide global daily SM at 9-km spatial resolution making it suitable for agricultural drought monitoring. However, while SMAP offers relatively high spatial resolution, it lacks long-term records (available since April 2015), whereas other long-term satellite products have coarser spatial resolution. So, this study evaluates the potential of short-term satellite SM data, specifically SMAP-SM, for agricultural drought characterization using two SM-based indices: Soil Water Deficit Index (SWDI) and Soil Moisture Deficit Index (SMDI). The Godavari basin is selected as study area, which is not so well gauged for SM data, and the agricultural drought in the basin is assessed from 2016 to 2021. The results revealed that both SWDI and SMDI indices effectively captured inter-annual/seasonal variations, demonstrating their robustness in comparison to precipitation-based indices rainfall anomalies (RA) and Standardized Precipitation Index (SPI). Spatial analysis reveals that western basin consistently experiences drought conditions, while the eastern region remains relatively wet. The drought area ratio (DAR) analysis across agro-ecological zones (AEZs) of basin reveals that SWDI is more sensitive to severe and extreme droughts, whereas SPI is more responsive to mild and moderate droughts. Zone-wise DAR showed SWDI and SMDI identified distinct drought conditions across all AEZs, whereas SPI and RA showed evenly distributed drought levels across AEZs, underscoring their broader, less soil-specific focus. These findings emphasize the potential of short-term satellite-based SM, as well as SM-derived indices in advancing agricultural drought characterization, offering valuable insights for policymakers in developing region-specific mitigation strategies and improving drought preparedness in other poorly gauged river basins.</p></div>","PeriodicalId":544,"journal":{"name":"Environmental Monitoring and Assessment","volume":"197 5","pages":""},"PeriodicalIF":3.0000,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Short-term satellite soil moisture for agricultural drought characterization over Godavari basin, India\",\"authors\":\"Hussain Palagiri, Manali Pal, Rajib Maity\",\"doi\":\"10.1007/s10661-025-14044-z\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Soil moisture (SM) is crucial for identifying agricultural drought, but due to the limited availability of large scale and high-resolution SM data, drought indices based on hydro-meteorological variables are commonly used. Recent advancements in microwave remote sensing, such as the Soil Moisture Active Passive (SMAP) satellite, provide global daily SM at 9-km spatial resolution making it suitable for agricultural drought monitoring. However, while SMAP offers relatively high spatial resolution, it lacks long-term records (available since April 2015), whereas other long-term satellite products have coarser spatial resolution. So, this study evaluates the potential of short-term satellite SM data, specifically SMAP-SM, for agricultural drought characterization using two SM-based indices: Soil Water Deficit Index (SWDI) and Soil Moisture Deficit Index (SMDI). The Godavari basin is selected as study area, which is not so well gauged for SM data, and the agricultural drought in the basin is assessed from 2016 to 2021. The results revealed that both SWDI and SMDI indices effectively captured inter-annual/seasonal variations, demonstrating their robustness in comparison to precipitation-based indices rainfall anomalies (RA) and Standardized Precipitation Index (SPI). Spatial analysis reveals that western basin consistently experiences drought conditions, while the eastern region remains relatively wet. The drought area ratio (DAR) analysis across agro-ecological zones (AEZs) of basin reveals that SWDI is more sensitive to severe and extreme droughts, whereas SPI is more responsive to mild and moderate droughts. Zone-wise DAR showed SWDI and SMDI identified distinct drought conditions across all AEZs, whereas SPI and RA showed evenly distributed drought levels across AEZs, underscoring their broader, less soil-specific focus. These findings emphasize the potential of short-term satellite-based SM, as well as SM-derived indices in advancing agricultural drought characterization, offering valuable insights for policymakers in developing region-specific mitigation strategies and improving drought preparedness in other poorly gauged river basins.</p></div>\",\"PeriodicalId\":544,\"journal\":{\"name\":\"Environmental Monitoring and Assessment\",\"volume\":\"197 5\",\"pages\":\"\"},\"PeriodicalIF\":3.0000,\"publicationDate\":\"2025-04-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Environmental Monitoring and Assessment\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s10661-025-14044-z\",\"RegionNum\":4,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Environmental Monitoring and Assessment","FirstCategoryId":"93","ListUrlMain":"https://link.springer.com/article/10.1007/s10661-025-14044-z","RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
Short-term satellite soil moisture for agricultural drought characterization over Godavari basin, India
Soil moisture (SM) is crucial for identifying agricultural drought, but due to the limited availability of large scale and high-resolution SM data, drought indices based on hydro-meteorological variables are commonly used. Recent advancements in microwave remote sensing, such as the Soil Moisture Active Passive (SMAP) satellite, provide global daily SM at 9-km spatial resolution making it suitable for agricultural drought monitoring. However, while SMAP offers relatively high spatial resolution, it lacks long-term records (available since April 2015), whereas other long-term satellite products have coarser spatial resolution. So, this study evaluates the potential of short-term satellite SM data, specifically SMAP-SM, for agricultural drought characterization using two SM-based indices: Soil Water Deficit Index (SWDI) and Soil Moisture Deficit Index (SMDI). The Godavari basin is selected as study area, which is not so well gauged for SM data, and the agricultural drought in the basin is assessed from 2016 to 2021. The results revealed that both SWDI and SMDI indices effectively captured inter-annual/seasonal variations, demonstrating their robustness in comparison to precipitation-based indices rainfall anomalies (RA) and Standardized Precipitation Index (SPI). Spatial analysis reveals that western basin consistently experiences drought conditions, while the eastern region remains relatively wet. The drought area ratio (DAR) analysis across agro-ecological zones (AEZs) of basin reveals that SWDI is more sensitive to severe and extreme droughts, whereas SPI is more responsive to mild and moderate droughts. Zone-wise DAR showed SWDI and SMDI identified distinct drought conditions across all AEZs, whereas SPI and RA showed evenly distributed drought levels across AEZs, underscoring their broader, less soil-specific focus. These findings emphasize the potential of short-term satellite-based SM, as well as SM-derived indices in advancing agricultural drought characterization, offering valuable insights for policymakers in developing region-specific mitigation strategies and improving drought preparedness in other poorly gauged river basins.
期刊介绍:
Environmental Monitoring and Assessment emphasizes technical developments and data arising from environmental monitoring and assessment, the use of scientific principles in the design of monitoring systems at the local, regional and global scales, and the use of monitoring data in assessing the consequences of natural resource management actions and pollution risks to man and the environment.