Nonstationary Standardized Soil Moisture Index (NSSMI-3) for the Krishna River Basin

This dataset contains the Nonstationary Standardized Soil Moisture Index (NSSMI) at a 3-month time scale (NSSMI-3) for the Krishna River Basin covering the period 1953–2024, developed to quantify agricultural drought conditions. The index accounts for nonstationarity in soil moisture dynamics, allowing distribution parameters to vary over time to better capture changing hydro-climatic conditions. Parameter estimation was performed using the Differential Evolution Markov Chain (DE-MC) method, while sampling was carried out using the Metropolis-Hastings algorithm within a Markov Chain Monte Carlo (MCMC) framework. Five Markov chains were run concurrently to ensure robust parameter estimation and convergence.本数据集包含覆盖1953–2024年的克里希纳河流域（Krishna River Basin）3个月时间尺度下的非平稳标准化土壤湿度指数（Nonstationary Standardized Soil Moisture Index, NSSMI，即NSSMI-3），该指数旨在量化农业干旱状况。 该指数考虑了土壤湿度动态过程中的非平稳性，允许分布参数随时间动态变化，从而更精准地捕捉不断演变的水文气候条件。参数估计工作采用差分进化马尔可夫链（Differential Evolution Markov Chain, DE-MC）方法完成，而抽样环节则在马尔可夫链蒙特卡洛（Markov Chain Monte Carlo, MCMC）框架内通过Metropolis-Hastings算法（Metropolis-Hastings algorithm）实现。为确保参数估计的稳健性与收敛性，研究同时运行了五条马尔可夫链。