{"title":"揭示印度土壤水分异常现象:对农业和水资源战略的影响","authors":"Saurabh Kumar Gupta, Suraj Kumar Singh, Shruti Kanga, Pankaj Kumar, Gowhar Meraj, Dhrubajyoti Sahariah, Jatan Debnath, Kesar Chand, Bhartendu Sajan, Saurabh Singh","doi":"10.1007/s00704-024-05088-1","DOIUrl":null,"url":null,"abstract":"<p>Soil moisture plays a critical role in agricultural productivity and water resource management, especially in a diverse and populous country like India. Understanding variations in soil moisture across different regions and seasons is essential for adapting agricultural practices and water management strategies to local conditions. This study examines changes in soil moisture levels across India, comparing contemporary data from 2023 with historical averages from 2000 to 2005 using advanced remote sensing and GIS technologies. The primary objective of this study is to identify Soil Moisture Anomalies (SMA) across India, quantify their impacts on agriculture and water resources, and provide recommendations for targeted management strategies. By comparing recent soil moisture data against historical averages, the study aims to highlight trends and changes that could influence future water resource planning and agricultural practices. The research utilizes data from the Famine Early Warning Systems Network’s (FEWS NET) i.e. Land Data Assimilation System (FLDAS), obtained from NASA’s data archives. The study employs a systematic approach to analyze seasonal variations in soil moisture across different Indian states. Soil moisture levels were analyzed using zonal statistics in GIS to classify regions into categories based on the degree of anomaly observed. This classification helped in understanding the spatial distribution of soil moisture during the pre-monsoon, monsoon, and post-monsoon seasons. The study found significant regional and seasonal variations in soil moisture across India. During the monsoon period, areas such as Bihar and Jharkhand consistently showed significant moisture deficits, indicative of drought conditions, affecting agricultural output and necessitating urgent water conservation measures. Conversely, regions like Punjab benefited from positive soil moisture anomalies, enhancing agricultural productivity. The pre-monsoon and post-monsoon seasons also showed variations, with some areas experiencing deficits requiring careful water management while others had surpluses that increased the risk of flooding. The analysis of SMA in India underscores the need for region-specific agricultural and water management strategies that consider significant variability in soil moisture conditions. The study highlights the importance of integrating soil moisture monitoring into national policy frameworks to enhance climate resilience and sustainable agricultural practices. Future research should focus on updating soil moisture assessments with more recent data and refining predictive models to improve the accuracy and effectiveness of water management and agricultural interventions.</p>","PeriodicalId":22945,"journal":{"name":"Theoretical and Applied Climatology","volume":"38 1","pages":""},"PeriodicalIF":2.8000,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Unearthing India’s soil moisture anomalies: impact on agriculture and water resource strategies\",\"authors\":\"Saurabh Kumar Gupta, Suraj Kumar Singh, Shruti Kanga, Pankaj Kumar, Gowhar Meraj, Dhrubajyoti Sahariah, Jatan Debnath, Kesar Chand, Bhartendu Sajan, Saurabh Singh\",\"doi\":\"10.1007/s00704-024-05088-1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Soil moisture plays a critical role in agricultural productivity and water resource management, especially in a diverse and populous country like India. Understanding variations in soil moisture across different regions and seasons is essential for adapting agricultural practices and water management strategies to local conditions. This study examines changes in soil moisture levels across India, comparing contemporary data from 2023 with historical averages from 2000 to 2005 using advanced remote sensing and GIS technologies. The primary objective of this study is to identify Soil Moisture Anomalies (SMA) across India, quantify their impacts on agriculture and water resources, and provide recommendations for targeted management strategies. By comparing recent soil moisture data against historical averages, the study aims to highlight trends and changes that could influence future water resource planning and agricultural practices. The research utilizes data from the Famine Early Warning Systems Network’s (FEWS NET) i.e. Land Data Assimilation System (FLDAS), obtained from NASA’s data archives. The study employs a systematic approach to analyze seasonal variations in soil moisture across different Indian states. Soil moisture levels were analyzed using zonal statistics in GIS to classify regions into categories based on the degree of anomaly observed. This classification helped in understanding the spatial distribution of soil moisture during the pre-monsoon, monsoon, and post-monsoon seasons. The study found significant regional and seasonal variations in soil moisture across India. During the monsoon period, areas such as Bihar and Jharkhand consistently showed significant moisture deficits, indicative of drought conditions, affecting agricultural output and necessitating urgent water conservation measures. Conversely, regions like Punjab benefited from positive soil moisture anomalies, enhancing agricultural productivity. The pre-monsoon and post-monsoon seasons also showed variations, with some areas experiencing deficits requiring careful water management while others had surpluses that increased the risk of flooding. The analysis of SMA in India underscores the need for region-specific agricultural and water management strategies that consider significant variability in soil moisture conditions. The study highlights the importance of integrating soil moisture monitoring into national policy frameworks to enhance climate resilience and sustainable agricultural practices. 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引用次数: 0
摘要
土壤水分对农业生产力和水资源管理起着至关重要的作用,尤其是在印度这样一个多元且人口众多的国家。了解不同地区和不同季节土壤水分的变化,对于因地制宜地调整农业生产方式和水资源管理策略至关重要。本研究利用先进的遥感和地理信息系统技术,将 2023 年的当代数据与 2000 年至 2005 年的历史平均数据进行比较,研究印度各地土壤水分水平的变化。本研究的主要目的是确定印度各地的土壤水分异常现象(SMA),量化其对农业和水资源的影响,并为有针对性的管理策略提供建议。通过将近期土壤水分数据与历史平均值进行比较,该研究旨在突出可能影响未来水资源规划和农业实践的趋势和变化。研究利用了从美国国家航空航天局数据档案中获得的饥荒预警系统网络(FEWS NET)即土地数据同化系统(FLDAS)的数据。该研究采用系统方法分析印度各邦土壤水分的季节性变化。利用地理信息系统(GIS)中的分区统计对土壤水分水平进行分析,根据观测到的异常程度将区域划分为不同类别。这种分类有助于了解季风前、季风和季风后季节土壤水分的空间分布。研究发现,印度各地的土壤水分存在明显的地区和季节差异。在季风期,比哈尔邦和恰尔肯德邦等地区持续出现严重的水分不足,显示出干旱状况,影响了农业产量,需要采取紧急节水措施。相反,旁遮普等地区则得益于积极的土壤水分异常,提高了农业生产率。季风前和季风后的季节也呈现出差异,一些地区出现缺水,需要谨慎管理水资源,而另一些地区则出现过剩,增加了洪水的风险。对印度 SMA 的分析强调,需要制定针对具体地区的农业和水资源管理战略,考虑土壤水分条件的显著变化。这项研究强调了将土壤水分监测纳入国家政策框架的重要性,以增强气候适应能力和可持续农业实践。未来的研究应侧重于利用最新数据更新土壤水分评估,并完善预测模型,以提高水资源管理和农业干预措施的准确性和有效性。
Unearthing India’s soil moisture anomalies: impact on agriculture and water resource strategies
Soil moisture plays a critical role in agricultural productivity and water resource management, especially in a diverse and populous country like India. Understanding variations in soil moisture across different regions and seasons is essential for adapting agricultural practices and water management strategies to local conditions. This study examines changes in soil moisture levels across India, comparing contemporary data from 2023 with historical averages from 2000 to 2005 using advanced remote sensing and GIS technologies. The primary objective of this study is to identify Soil Moisture Anomalies (SMA) across India, quantify their impacts on agriculture and water resources, and provide recommendations for targeted management strategies. By comparing recent soil moisture data against historical averages, the study aims to highlight trends and changes that could influence future water resource planning and agricultural practices. The research utilizes data from the Famine Early Warning Systems Network’s (FEWS NET) i.e. Land Data Assimilation System (FLDAS), obtained from NASA’s data archives. The study employs a systematic approach to analyze seasonal variations in soil moisture across different Indian states. Soil moisture levels were analyzed using zonal statistics in GIS to classify regions into categories based on the degree of anomaly observed. This classification helped in understanding the spatial distribution of soil moisture during the pre-monsoon, monsoon, and post-monsoon seasons. The study found significant regional and seasonal variations in soil moisture across India. During the monsoon period, areas such as Bihar and Jharkhand consistently showed significant moisture deficits, indicative of drought conditions, affecting agricultural output and necessitating urgent water conservation measures. Conversely, regions like Punjab benefited from positive soil moisture anomalies, enhancing agricultural productivity. The pre-monsoon and post-monsoon seasons also showed variations, with some areas experiencing deficits requiring careful water management while others had surpluses that increased the risk of flooding. The analysis of SMA in India underscores the need for region-specific agricultural and water management strategies that consider significant variability in soil moisture conditions. The study highlights the importance of integrating soil moisture monitoring into national policy frameworks to enhance climate resilience and sustainable agricultural practices. Future research should focus on updating soil moisture assessments with more recent data and refining predictive models to improve the accuracy and effectiveness of water management and agricultural interventions.
期刊介绍:
Theoretical and Applied Climatology covers the following topics:
- climate modeling, climatic changes and climate forecasting, micro- to mesoclimate, applied meteorology as in agro- and forestmeteorology, biometeorology, building meteorology and atmospheric radiation problems as they relate to the biosphere
- effects of anthropogenic and natural aerosols or gaseous trace constituents
- hardware and software elements of meteorological measurements, including techniques of remote sensing