Drought Monitoring for Washington State: Indicators and Applications
Drought Monitoring for Washington State: Indicators and Applications
复制标题
DOI：
10.1175/2010jhm1307.1
复制
发表时间：
2011-02
影响因子：
3.8
通讯作者：
S. Shukla;A. Steinemann;D. Lettenmaier
中科院分区：
文献类型：
--
作者：
S. Shukla;A. Steinemann;D. Lettenmaier
摘要干旱监测系统（DMS）可以帮助检测和描述干旱状况，减少干旱的不利影响。作者评估如何DMS的华盛顿州，基于陆面模型（LSM），将执行。LSM代表当前的土壤湿度（SM），雪水当量（SWE）和径流。DMS结合了标准化降水指数（SPI）、标准化径流指数（SRI）和取自LSM的土壤水分百分位数（SMP）。四个历史干旱事件（1976-77年，1987-89年，2000-01年和2004-05年）构建使用DMS指标SPI/SRI-3，SPI/SRI-6，SPI/SRI-12，SPI/SRI-24，SPI/SRI-36和SMP，每月更新，在每个国家的62个水资源清单区（WRIAs）。作者还将基于DMS指标的干旱触发因素与四次干旱期间干旱条件和管理决策的演变进行了比较。结果表明，DMS将检测到干旱条件的开始和恢复，在M。
Abstract A drought monitoring system (DMS) can help to detect and characterize drought conditions and reduce adverse drought impacts. The authors evaluate how a DMS for Washington State, based on a land surface model (LSM), would perform. The LSM represents current soil moisture (SM), snow water equivalent (SWE), and runoff over the state. The DMS incorporates the standardized precipitation index (SPI), standardized runoff index (SRI), and soil moisture percentile (SMP) taken from the LSM. Four historical drought events (1976–77, 1987–89, 2000–01, and 2004–05) are constructed using DMS indicators of SPI/SRI-3, SPI/SRI-6, SPI/SRI-12, SPI/SRI-24, SPI/SRI-36, and SMP, with monthly updates, in each of the state’s 62 Water Resource Inventory Areas (WRIAs). The authors also compare drought triggers based on DMS indicators with the evolution of drought conditions and management decisions during the four droughts. The results show that the DMS would have detected the onset and recovery of drought conditions, in m...