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Assessing climate change risk to municipal water supplies is often conducted by hydrologic modeling specific to local watersheds and infrastructure to ensure that outputs are compatible with existing planning frameworks and processes. This study leverages the modeling capacity of an operational National Weather Service River Forecast Center to explore the potential impacts of future climate-driven hydrologic changes on factors important to planning at the Salt Lake City Department of Public Utilities (SLC). Hydrologic modeling results for the study area align with prior research in showing that temperature changes alone will lead to earlier runoff and reduced runoff volume. The sensitivity of average annual flow to temperature varies significantly between watersheds, averaging -3.8% °F-1 and ranging from 21.8% to 26.5% flow reduction per degree Fahrenheit of warming. The largest flow reductions occur during the high water demand months of May-September. Precipitation drives hydrologic response more strongly than temperature, with each 1% precipitation change producing an average 1.9% runoff change of the same sign. This paper explores the consequences of climate change for the reliability of SLC's water supply system using scenarios that include hydrologic changes in average conditions, severe drought scenarios, and future water demand test cases. The most significant water management impacts will be earlier and reduced runoff volume, which threaten the system's ability to maintain adequate streamflow and storage to meet late-summer water demands. [ABSTRACT FROM AUTHOR]

In this study, a nonstationary standardized precipitation index (NSPI) is calculated by fitting precipitation data to the nonstationary gamma model with climate indices as covariates and compared with stationary standardized precipitation index (SSPI) in fitting observed precipitation and identifying meteorological droughts during 1964-2016 in the Yangtze River basin (YRB). Results show that changing trends of NSPI are roughly consistent with those of SSPI, but the NSPI performs better than SSPI for fitting precipitation. Using the NSPI, spatiotemporal variations and joint return period of drought characteristics are investigated by using modified Mann-Kendall and copula function. It is found that the west YRB experiences mostly severe droughts but shows a mitigating tendency, while in the north-central region, moderate droughts are dominant but have an aggravating tendency. Drought peak shares a spatial distribution pattern similar to intensity, with higher averages in the west and south-central basin and lower averages in the north-central part, but they exhibit a higher occurrence frequency of droughts. The joint return periods of drought characteristics reveal that slight and moderate droughts with duration D of no more than 3 months are more likely to occur in the YRB with return periods of 2-25 years. The severe- and extreme-intensity droughts with more than 3-month duration occur rarely in the YRB, but extreme peak droughts with slight or moderate intensity could hit most of the basin in 100 years. In addition, for most drought scenarios, droughts exhibit longer return periods in the north-central and southeast parts relative to other regions of the YRB. [ABSTRACT FROM AUTHOR]

Recent events across many regions around the world have shown that short-term droughts (i.e., daily or weekly) with sudden occurrence can lead to huge losses to a wide array of environmental and societal sectors. However, the most commonly used drought indices can only identify drought at the monthly scale. Here, we introduced a daily scale drought index, that is, the standardized antecedent precipitation evapotranspiration index (SAPEI) that utilizes precipitation and potential evapotranspiration and also considers the effect of early water balance on dry/wet conditions on the current day. The robustness of SAPEI is first assessed through comparison with two typical monthly indices [Palmer drought severity index (PDSI) and standardized precipitation evapotranspiration index (SPEI)] and soil moisture, and then applied to tracking short-term droughts during 1961–2015 for the Pearl River basin in south China. It is demonstrated that SAPEI performs as well as SPEI/self-calibrating PDSI at the monthly scale but outperforms SPEI at the weekly scale. Moreover, SAPEI is capable of revealing daily drought conditions, fairly consistent with soil moisture changes. Results also show that many of the historical short-term droughts over the Pearl River basin have multiple peaks in terms of severity, affected area, and intensity. The daily scale SAPEI provides an effective way of exploring drought initiation, development, and decay, which could be conducive for decision-makers and stakeholders to make early and timely warnings. [ABSTRACT FROM AUTHOR]

Flash droughts are extreme phenomena that have been identified using two different approaches. The first approach identifies these events based on unusually rapid intensification rates, whereas the second approach implicitly identifies short-term features. This latter approach classifies flash droughts into two types, namely, precipitation deficit and heat wave flash droughts (denoted as PDFD and HWFD). In this study, we evaluate these two approaches over the Yellow River basin (YRB) to determine which approach provides more accurate information about flash droughts and why. Based on the concept of intensification rate, a new quantitative flash drought identification method focused on soil moisture depletion during the onset–development phase is proposed. Its performance was evaluated by comparing the onset time and spatial dynamics of the identified flash droughts with PDFD and HWFD events identified using the second approach. The results show that the rapid-intensification approach is better able to capture the continuous evolution of a flash drought. Since the approach for identifying PDFD and HWFD events does not consider changes in soil moisture with time, it cannot ensure that the events exhibit rapid intensification, nor can it effectively capture flash droughts' onset. Evaluation of the results showed that the chosen hydrometeorological variables and corresponding thresholds, particularly that of temperature, are the main reasons for the poor performance of the PDFD and HWFD identification approach. This study promotes a deeper understanding of flash droughts that is beneficial for drought monitoring, early warning, and mitigation. [ABSTRACT FROM AUTHOR]

The future changes in drought characteristics were examined on a regional scale for South Korea, in northeastern Asia, using 17 bias-corrected projections from phase 5 of the Coupled Model Intercomparison Project (CMIP5) of representative concentration pathway (RCP) scenarios 4.5 and 8.5. The frequency of severe or extreme drought, based on the standardized precipitation index (SPI) and standardized precipitation evapotranspiration index (SPEI), with time scales of 1, 3, and 12 months (i.e., SPI1, SPI3, SPI12, SPEI1, SPEI3, and SPEI12), was considered, as well as the average duration based on SPEI1. A multimodel ensemble (MME) was produced using selected models, and future changes were investigated in terms of both drought frequency and the average duration for the entire area and four river basins. The changes in drought frequency largely depend on the selection of a drought index, rather than climate projection scenarios. SPEI3 mostly projected future increases in drought frequency, while SPI3 showed varied projections. SPI12 projected decreases in drought frequency for both scenarios in the study area, while differences between river basins were observed for SPEI12. Increases in the average duration of droughts were projected based on SPEI1, indicating an increase in persistent short-term droughts in the future. The results emphasize the importance of regional- and subregional-scale analysis in northeastern Asia. The findings of the study provide valuable information that can be used for drought-related decision-making, which could not be obtained from studies on a global spatial scale. [ABSTRACT FROM AUTHOR]

Drought indices are often used for monitoring interannual variability in macroscale hydrology. However, the diversity of drought indices raises several issues: 1) which indices perform best and where; 2) does the incorporation of potential evapotranspiration (PET) in indices strengthen relationships, and how sensitive is the choice of PET methods to such results; 3) what additional value is added by using higher-spatial-resolution gridded climate layers; and 4) how have observed relationships changed through time. Standardized precipitation index, standardized precipitation evapotranspiration index (SPEI), Palmer drought severity index, and water balance runoff (WBR) model output were correlated to water-year runoff for 21 unregulated drainage basins in the Pacific Northwest of the United States. SPEI and WBR with time scales encompassing the primary precipitation season maximized the explained variance in water-year runoff in most basins. Slightly stronger correlations were found using PET estimates from the Penman-Monteith method over the Thornthwaite method, particularly for time periods that incorporated the spring and summer months in basins that receive appreciable precipitation during the growing season. Indices computed using high-resolution climate surfaces explained over 10% more variability than metrics derived from coarser-resolution datasets. Increased correlation in the latter half of the study period was partially attributable to increased streamflow variability in recent decades as well as to improved climate data quality across the interior mountain watersheds. [ABSTRACT FROM AUTHOR]

The main objective of this study is to evaluate the uncertainties due to sample size associated with the estimation of the standardized precipitation index (SPI) and their impact on the level of confidence in drought monitoring in Africa using high-spatial-resolution data from short time series. To do this, two different rainfall datasets, each available on a monthly basis, were analyzed over four river basins in Africa-Oum er-Rbia, Limpopo, Niger, and eastern Nile-as well as at the continental level. The two precipitation datasets used were the Tropical Rainfall Measuring Mission (TRMM) satellite monthly rainfall product 3B43 and the Global Precipitation Climatology Centre full-reanalysis gridded precipitation dataset. A nonparametric resampling bootstrap approach was used to compute the confidence bands associated with the SPI estimation, which are essential for making a qualified assessment of drought events. The comparative analysis of different datasets suggests that for reliable drought monitoring over Africa it is feasible to use short time series of remote sensing precipitation data, such as those from TRMM, that have a higher spatial resolution than other gridded precipitation data. The proposed approach for drought monitoring has the potential to be used in support of decision making at both continental and subcontinental scales over Africa or over other regions that have a sparse distribution of rainfall measurement instruments. [ABSTRACT FROM AUTHOR]

A modified drought index, named the spatially normalized--standardized precipitation index (SN-SPI), has been developed for assessing meteorological droughts. The SN--SPI is a variant index to the standardized precipitation index and is based on the probability of precipitation at different time scales, but it is spatially normalized for improved assessment of drought severity. Results of this index incorporate the spatial distribution of precipitation and produce improved drought warnings. This index is applied in the island of Crete, Greece, and the drought results are compared to the ones of SPI. A 30-year-long average monthly precipitation dataset from 130 watersheds of the island is used by the above indices for drought classification in terms of its duration and intensity. Bias-adjusted monthly precipitation estimates from an ensemble of 10 regional climate models were used to quantify the influence of global warming to drought conditions over the period 2010--2100. Results based on both indices (calculated for three time scales of 12, 24, and 48 months) from 3 basins in west, central, and east parts of the island show that 1) the extreme drought periods are the same (reaching 7%% of time) but the intensities based on SN--SPI are lower; 2) the area covered by extreme droughts is 3%% (first time scale), 16%% (second time scale), and 25%% (third time scale), and 96%% (first time scale), 95%% (second time scale), and 80%% (third time scale) based on the SN--SPI and SPI, respectively; 3) concerning the longest time scale (48 months), more than half of the area of Crete is about to experience drought conditions during 28%%, 69%%, and 97%% for 2010--40, 2040--70, and 2070--2100, respectively; and 4) extremely dry conditions will cover 52%%, 33%%, and 25%% of the island for the future 90-year period using 12-, 24-, and 48-month SN--SPI, respectively. [ABSTRACT FROM AUTHOR]