Michael L. Anderson

Physically Based Estimation of Maximum Precipitation over Three Watersheds in Northern California: Atmospheric Boundary Condition Shifting

AbstractMaximum precipitation during a historical period is estimated by means of a physically based regional atmospheric model over three watersheds in Northern California: the American River watershed (ARW), the Yuba River watershed (YRW), and the Upper Feather River watershed (UFRW). In Northern California, severe storm events are mostly caused by a high-moisture atmospheric flow from the Pacific Ocean, referred to as atmospheric river (AR). Therefore, a method to maximize the contribution of an AR on precipitation over each of the targeted watersheds is proposed. The method shifts the atmospheric boundary conditions of the regional atmospheric model in space with latitude and longitude so that the AR strikes each of the targeted watersheds in an optimal direction and location to maximize the precipitation over these watersheds. For this purpose, the fifth generation Penn State/National Center for Atmospheric Research (NCAR) Mesoscale Model (MM5) is used as the regional atmospheric model, and the NCAR/...

Future climate: projected average

Global climate models (GCMs) are the fundamental drivers of regional climate-change projections (IPCC 2007). GCMs allow us to characterize changes in atmospheric circulation associated with human causes at global and continental scales. However, because of the planetary scope of the GCMs, their resolution, or level of detail, is somewhat coarse. A typical GCM grid spacing is about 62 miles (100 km) or greater, which is inadequate for creating projections and evaluating impacts of climate change at a regional scale. Thus, a “downscaling” procedure is needed to provide finer spatial detail of the model results.

Coupled Regional Hydroclimate Model and Its Application to the Tigris-Euphrates Basin

To establish a basinwide water management plan for the Tigris-Euphrates (TE) watershed, it is necessary to perform rigorous water balance studies of the whole watershed—at least for critical historical drought and flood conditions and under various water resources development scenarios. Water-balance studies over the watershed require climatic and hydrologic data sets, corresponding to historical critical flood and drought periods, at fine time and spatial grid resolutions provide the necessary hydroclimatic information. The Regional Hydroclimate Model of the Tigris-Euphrates (RegHCM-TE) and the associated geographic information system (GIS) were developed to downscale large-scale atmospheric data sets over the TE watershed and to reconstruct the aforementioned climatic and land hydrologic data sets at fine spatial and time increments. In RegHCM-TE, the earth system over the TE watershed is modeled as a fully coupled system of atmospheric processes aloft coupled with the atmospheric boundary layer, land-s...

Future Climate: Projected Extremes

Extreme events can be defined in many ways. Typical definitions of weather and climate extremes consider either the maximum value during a specified time interval (such as season or year) or exceedance of a threshold (the “peaks-over-threshold” [POT] approach), in which universal rather than local thresholds are frequently applied. For example, temperatures above 95°F (35°C) are often considered extreme in most locations across the United States, except in areas such as the low-lying deserts of Arizona and California, where such temperatures are typical in the summer. Temperatures at these levels are obviously extreme for living organisms from a non-adapted, physiological perspective, and technological adaptation for humans is required for day-to-day functioning in such temperatures. But such temperatures are not necessarily extreme from the statistical or local climate perspectives. In statistics, extremes are considered low-probability events that differ greatly from typical occurrences. The IPCC defines extremes as 1% to 10% of the largest or smallest values of a distribution (Trenberth et al. 2007). Studies over large or complex regions marked by significant climatic variation require definitions that are relevant to local climate. Across the Southwest, location-specific definitions of extreme temperature, precipitation, humidity, and wind are required if a meaningful region-wide perspective is desired.

Introduction to Hydrology

Hydrology deals with the occurrence, movement, and storage of water in the earth system. Hydrologic science comprises understanding the underlying physical and stochastic processes involved and estimating the quantity and quality of water in the various phases and stores. The study of hydrology also includes quantifying the effects of such human interventions on the natural system at watershed, river basin, regional, country, continental, and global scales. The process of water circulating from precipitation in the atmosphere falling to the ground, traveling through a river basin (or through the entire earth system), and then evaporating back to the atmosphere is known as the hydrologic cycle. This introductory chapter includes seven subjects, namely, hydroclimatology, surface water hydrology, soil hydrology, glacier hydrology, watershed and river basin modeling, risk and uncertainty analysis, and data acquisition and information systems. The emphasis is on recent developments particularly on the role that atmospheric and climatic processes play in hydrology, the advances in hydrologic modeling of watersheds, the experiences in applying statistical concepts and laws for dealing with risk and uncertainty and the challenges encountered in dealing with nonstationarity, and the use of newer technology (particularly spaceborne sensors) for detecting and estimating the various components of the hydrologic cycle such as precipitation, soil moisture, and evapotranspiration.

Long-term trend analysis on total and extreme precipitation over Shasta Dam watershed

Californias interconnected water system is one of the most advanced water management systems in the world, and understanding of long-term trends in atmospheric and hydrologic behavior has increasingly being seen as vital to its future well-being. Knowledge of such trends is hampered by the lack of long-period observation data and the uncertainty surrounding future projections of atmospheric models. This study examines historical precipitation trends over the Shasta Dam watershed (SDW), which lies upstream of one of the most important components of Californias water system, Shasta Dam, using a dynamical downscaling methodology that can produce atmospheric data at fine time-space scales. The Weather Research and Forecasting (WRF) model is employed to reconstruct 159years of long-term hourly precipitation data at 3km spatial resolution over SDW using the 20th Century Reanalysis Version 2c dataset. Trend analysis on this data indicates a significant increase in total precipitation as well as a growing intensity of extreme events such as 1, 6, 12, 24, 48, and 72-hour storms over the period of 1851 to 2010. The turning point of the increasing trend and no significant trend periods is found to be 1940 for annual precipitation and the period of 1950 to 1960 for extreme precipitation using the sequential Mann-Kendall test. Based on these analysis, we find the trends at the regional scale do not necessarily apply to the watershed-scale. The sharp increase in the variability of annual precipitation since 1970s is also detected, which implies an increase in the occurrence of extreme wet and dry conditions. These results inform long-term planning decisions regarding the future of Shasta Dam and Californias water system.

Role of Snowmelt in Determining whether the Maximum Precipitation Always Results in the Maximum Flood

AbstractIn snow-dominated regions surface air temperature is expected to have a substantial effect on the magnitude of a flood during a storm event. It is risky to estimate the design flood based only on the maximum precipitation while excluding other atmospheric variables like temperature and radiation. To overcome this problem, a methodology to estimate the maximum flood is proposed based on a physically based hydrologic model with input from physically maximized storm events by means of a numerical atmospheric model. As a case study, the probable maximum floods are simulated for the Upper Feather River watershed, the Yuba River watershed, and the American River watershed that are located in a mountainous region in Northern California, from the most severe 60 historical precipitation events during 1951–2010 for each watershed. The results show that this methodology can explain the underlying physical causes for the occurrence of maximum precipitation. It also shows that the maximum precipitation, determ...

Characterization of Extreme Storm Events Using a Numerical Model–Based Precipitation Maximization Procedure in the Feather, Yuba, and American River Watersheds in California

AbstractImprovements on nonhydrostatic atmospheric models such as MM5 in the last few decades have enhanced our understanding of the precipitation mechanism affected by topography and nonlinear dynamics of the atmosphere. This study addresses the use of such a regional atmospheric model to estimate physical maximum precipitation rates for the next generation of flood management strategies under evolving climate conditions. First, 48 significant historical storm events were selected based on the continuous reconstructed precipitation conditions on the Feather, Yuba, and American River watersheds in California. Then, the boundary conditions of the numerical atmospheric model were modified with the fully saturated atmospheric layers (100% relative humidity) to generate the atmospheric conditions that maximize the precipitation over the three watersheds. Surprisingly, maximizing the atmospheric moisture supply at the model boundary does not always increase the precipitation in the watersheds of interest. A ra...

Analysis of future climate change impacts on snow distribution over mountainous watersheds in Northern California by means of a physically-based snow distribution model

The impacts of climate change on snow distribution through the 21st century were investigated over three mountainous watersheds in Northern California by means of a physically-based snow distribution model. The future climate conditions during a 90-year future period from water year 2010 to 2100 were obtained from 13 future climate projection realizations from two GCMs (ECHAM5 and CCSM3) based on four SRES scenarios (A1B, A1FI, A2, and B1). The 13 future climate projection realizations were dynamically downscaled at 9 km resolution by a regional climate model. Using the downscaled variables based on the 13 future climate projection realizations, snow distribution over the Feather, Yuba, and American River watersheds (FRW, YRW, and ARW) was projected by means of the physically-based snow model. FRW and YRW watersheds cover the main source areas of the California State Water Project (SWP), and ARW is one of the key watersheds in the California Central Valley Project (CVP). SWP and CVP are of great importance as they provide and regulate much of the Californias water for drinking, irrigation, flood control, environmental, and hydro-power generation purposes. Ensemble average snow distribution over the study watersheds was calculated over the 13 realizations and for each scenario, revealing differences among the scenarios. While the snow reduction through the 21st century was similar between A1B and A2, the snow reduction was milder for B1, and more severe for A1FI. A significant downward trend was detected in the snowpack over nearly the entire watershed areas for all the ensemble average results.

Integrating global land-cover and soil datasets to update saturated hydraulic conductivity parameterization in hydrologic modeling

Soil properties play an important role in watershed hydrology and environmental modeling. In order to model realistic hydrologic processes, it is necessary to obtain compatible soil data. This study introduces a new method that integrates global soil databases with land use/land cover (LULC) databases to better represent saturated hydraulic conductivity (Ks) which is one of the most important soil properties in hydrologic modeling. The Ks is modified by means of uniting physical infiltration mechanisms with hydrologic soil-LULC complexes from lookup tables from USDA-SCS (1985). This approach enables assimilation of available coarse resolution soil parameters by the finer resolution global LULC datasets. In order to test the performance of the proposed approach, it has been incorporated into the Watershed Environmental Hydrology (WEHY) model to simulate hydrologic conditions over the Cache Creek Watershed (CCW) and Shasta Dam Watershed (SDW) in Northern California by means of different soil datasets. Soil dataset S1 was obtained from the local soil database including SSURGO (Web soil survey, USDA). The second soil dataset (S2) is the global ISRIC soil data SoilGrids-1km obtained from World Soil Information. Soil dataset S4 is global FAO soil data. The third (S3) and fifth (S5) soil datasets were calculated by integrating the LULC into global soil datasets (S2, S4), respectively. The results of this study suggest that the proposed approach can provide a fine resolution soil dataset through integration of LULC and soil data, which can improve the estimation of soil hydraulic parameters and the performance of hydrologic modeling over the target watersheds. Within this framework, the new approach of this study can be applied widely in many parts of the world by means of the global soil and LULC databases.