Climate Change,Atmospheric Rivers,and Floods in California – A Multimodel Analysis of Storm Frequency and Magnitude Changes1

Dettinger, Michael, 2011. Climate Change, Atmospheric Rivers, and Floods in California – A Multimodel Analysis of Storm Frequency and Magnitude Changes. Journal of the American Water Resources Association (JAWRA) 47(3):514‐523. DOI: 10.1111/j.1752‐1688.2011.00546.x Abstract: Recent studies have documented the important role that “atmospheric rivers” (ARs) of concentrated near‐surface water vapor above the Pacific Ocean play in the storms and floods in California, Oregon, and Washington. By delivering large masses of warm, moist air (sometimes directly from the Tropics), ARs establish conditions for the kinds of high snowlines and copious orographic rainfall that have caused the largest historical storms. In many California rivers, essentially all major historical floods have been associated with AR storms. As an example of the kinds of storm changes that may influence future flood frequencies, the occurrence of such storms in historical observations and in a 7‐model ensemble of historical‐climate and projected future climate simulations is evaluated. Under an A2 greenhouse‐gas emissions scenario (with emissions accelerating throughout the 21st Century), average AR statistics do not change much in most climate models; however, extremes change notably. Years with many AR episodes increase, ARs with higher‐than‐historical water‐vapor transport rates increase, and AR storm‐temperatures increase. Furthermore, the peak season within which most ARs occur is commonly projected to lengthen, extending the flood‐hazard season. All of these tendencies could increase opportunities for both more frequent and more severe floods in California under projected climate changes.     

Hydrologic Modeling of an Extreme Flood in the Guadalupe River in Texas1

Sharif, Hatim O., Almoutaz A. Hassan, Sazzad Bin-Shafique, Hongjie Xie, and Jon Zeitler, 2010. Hydrologic Modeling of an Extreme Flood in the Guadalupe River in Texas. Journal of the American Water Resources Association (JAWRA) 1-11. DOI: 10.1111/j.1752-1688.2010.00459.x Abstract: Many of the storms creating the greatest rainfall depths in Texas, measured over durations ranging from one minute to 48 hours, have occurred in the Texas Hill Country area. The upstream portion of the Guadalupe River Basin, located in the Texas Hill Country, is susceptible to flooding and rapid runoff due to thin soils, exposed bedrock, and sparse vegetation, in addition to the Balcones Escarpment uplift contributing to precipitation enhancement. In November 2004, a moist air mass from the Gulf of Mexico combined with moist air from the Pacific Ocean resulted in the wettest November in Texas since 1895. Although the peak discharges were not the highest on record, the U.S. Geological Survey (USGS) stream gauge on the Guadalupe River at Gonzales, Texas reported a daily mean discharge of 2,304 m³/s on November 23, 2004 (average discharge is 53 m³/s). In this paper, we examine the meteorological conditions that led to this event and apply a two-dimensional, physically based, distributed-parameter hydrologic model to simulate the response of a portion of the basin during this event. The study results clearly demonstrate the ability of physically based, distributed-parameter simulations, driven by operational radar rainfall products, to adequately model the cumulative effect of two rainfall events and route inflows from three upstream watersheds without the need for significant calibration.     

Estimating Lag to Peak between Rainfall and Peak Streamflow with a Mixed‐Effects Model

We test the use of a mixed‐effects model for estimating lag to peak for small basins in Maine (drainage areas from 0.8 to 78 km²). Lag to peak is defined as the time between the center of volume of the excess rainfall during a storm event and the resulting peak streamflow. A mixed‐effects model allows for multiple observations at sites without violating model assumptions inherent in traditional ordinary least squares models, which assume each observation is independent. The mixed model includes basin drainage area and maximum 15‐min rainfall depth for individual storms as explanatory features. Based on a remove‐one‐site cross‐validation analysis, the prediction errors of this model ranged from ?42% to +73%. The mixed model substantially outperformed three published models for lag to peak and one published model for centroid lag for estimating lag to peak for small basins in Maine. Lag to peak estimates are a key input to rainfall–runoff models used to design hydraulic infrastructure. The improved accuracy and consistency with model assumptions indicates that mixed models may provide increased data utilization that could enhance models and estimates of lag to peak in other regions.     

Evaluation of Satellite‐Derived Rainfall Data for Multiple Physio‐Climatic Regions in the Santiago River Basin,Mexico

Assessment of water resources requires reliable rainfall data, and rain gauge networks may not provide adequate spatial representation due to limited point measurements. The Tropical Rainfall Measuring Mission (TRMM) provides rainfall data at global scale, and has been used with good results. However, TRMM data are an indirect measurement of rainfall, and therefore must be validated for its proper use. In this work, a validation scheme was designed and implemented to compare the TRMM Version 7 (V7) monthly rainfall product at different time frames with data measured in two hydrologic subregions of the Santiago River Basin (SRB) in Mexico: Río Alto Santiago and Río Bajo Santiago (RBS). Additionally, three physio‐climatic regions provide an assessment of the interplay of topography, distance from coastal regions, and seasonal weather patterns on the correspondence between both datasets. The TRMM V7 rainfall product exhibited good agreement with the rain gauge data particularly for the RBS and for the whole SRB during wettest summer and autumn seasons. However, strong regional dependence was observed due to differences in climate and topography. Overall, in spite of some noted underestimations, the monthly TRMM V7 rainfall product was found to provide useful information that can be used to complement limited monitoring as is the case of RBS. An improved combined rainfall product could be generated and thus gaining the most benefits from both data sources.     

Effectiveness of Multi‐Site Weather Generator for Hydrological Modeling1

Khalili, Malika, François Brissette, and Robert Leconte, 2011. Effectiveness of Multi‐site Weather Generator for Hydrological Modeling. Journal of the American Water Resources Association (JAWRA) 1‐12. DOI: 10.1111/j.1752‐1688.2010.00514.x Abstract: A multi‐site weather generator has been developed using the concept of spatial autocorrelation. The multi‐site generation approach reproduces the spatial autocorrelations observed between a set of weather stations as well as the correlations between each pair of stations. Its performance has been assessed in two previous studies using both precipitation and temperature data. The main objective of this paper is to assess the efficiency of this multi‐site weather generator compared to a uni‐site generator with respect to hydrological modeling. A hydrological model, known as Hydrotel, was applied over the Chute du Diable watershed, located in the Canadian province of Quebec. The distributed nature of Hydrotel accounts for the spatial variations throughout the watershed, and thus allows a more in‐depth assessment of the effect of spatially dependent meteorological input on runoff generation. Simulated streamflows using both the multi‐site and uni‐site generated weather data were statistically compared to flows modeled using observed data. Overall, the hydrological modeling using the multi‐site weather generator significantly outperformed that using the uni‐site generator. This latter combined to Hydrotel resulted in a significant underestimation of extreme streamflows in all seasons.     

2013年秦皇岛连续两次降水过程对比分析

利用常规气象观测资料、自动站资料及卫星资料,从大尺度环流背景和水汽、动力、热力条件出发,对2013年8月底东北冷涡影响下秦皇岛两次降水过程进行对比分析。结果表明：由于处在东北冷涡发展的不同阶段,中低层温度场配置不同,两次过程降水特点极不相同。8月27日降水是一次连续的区域性降水过程,以层状云降水为主,降水均匀连续,8月31日至9月2日是冷涡后部西北气流影响下的数日局地性对流降水,具有很强的突发性。     

Effect of Light on Biodegradation of Estrone, 17β‐Estradiol,and 17α‐Ethinylestradiol in Stream Sediment

Biodegradation of [A‐ring ¹⁴C] Estrone (E1), 17β‐estradiol (E2), and 17α‐ethinylestradiol (EE2) to ¹⁴CO₂ was investigated under light and dark conditions in microcosms containing epilithon or sediment collected from Boulder Creek, Colorado. Mineralization of the estrogen A‐ring was observed in all sediment treatments, but not epilithon treatments. No difference in net mineralization between light and dark treatments was observed for ¹⁴C‐E2. Net mineralization of ¹⁴C‐E1 and ¹⁴C‐EE2 was enhanced in light treatments. Extents of ¹⁴CO₂ accumulation and rates of mineralization were significantly greater for E2 than E1 under dark conditions, but were comparable under light conditions. These results indicate substantial differences in the uptake and metabolism of E1 and E2 in the environment and suggest biorecalcitrance of E1 relative to E2 in light‐limited environments. The extent of ¹⁴CO₂ accumulation and rate of mineralization for EE2 in dark treatments were less than half of that observed for E2 and generally lower than for E1, consistent with previous reports of EE2 biorecalcitrance. However, ¹⁴CO₂ accumulation and rates of mineralization were comparable for EE2, E2, and E1 under light conditions. These results indicate photoactivation and/or phototransformation/photodegradation processes can substantially enhance heterotrophic biodegradation of estrogens in sunlit environments and may play an important role in estrogen transport and attenuation.     

Trends in Rainfall Exceedances in the Observed Record in Selected Areas of the United States1

Bonnin, Geoffrey M., Kazungu Maitaria, and Michael Yekta, 2011. Trends in Rainfall Exceedances in the Observed Record in Selected Areas of the United States. Journal of the American Water Resources Association (JAWRA) 47(6): 1173–1182. DOI: 10.1111/j.1752‐1688.2011.00603.x Abstract: Semantic differences have led to a gap in the understanding of the impacts of climate change on precipitation frequency estimates. There is popular perception that heavy rainfalls have become more frequent, and that this trend will increase with global warming. Most of the literature examines this question from the point of view of climatology using definitions of “heavy,”“very heavy,” or “extreme” rainfall, which are different from those commonly used by civil engineers. This article identifies the differences in meaning used by the climate and civil engineering communities and examines trends in the observed record in the frequency of exceedances (not trends in magnitudes). Using concepts recognized as the basis for design of the Nation’s civil infrastructure, we look at trends in the number of exceedances of thresholds for a variety of precipitation frequencies and event durations used by civil engineers. We found that the estimated trends in exceedances at one‐day and multiday durations were statistically significant and increasing for the Ohio River Basin and surrounding states but the reverse was true for the Semiarid Southwest (i.e., not significant and decreasing trends). In addition, we found the magnitude of the trends was small for all but the more frequent events and also small with respect to the uncertainty associated with the precipitation frequency estimates themselves.     

Sensitivity and Uncertainty of Ground‐Water Discharge Estimates for Semiarid Shrublands1

Abstract: We proposed a step‐by‐step approach to quantify the sensitivity of ground‐water discharge by evapotranspiration (ET) to three categories of independent input variables. To illustrate the approach, we adopt a basic ground‐water discharge estimation model, in which the volume of ground water lost to ET was computed as the product of the ground‐water discharge rate and the associated area. The ground‐water discharge rate was assumed to equal the ET rate minus local precipitation. The objective of this study is to outline a step‐by‐step procedure to quantify the contributions from individual independent variable uncertainties to the uncertainty of total ground‐water discharge estimates; the independent variables include ET rates of individual ET units, areas associated with the ET units, and precipitation in each subbasin. The specific goal is to guide future characterization efforts by better targeting data collection for those variables most responsible for uncertainty in ground‐water discharge estimates. The influential independent variables to be included in the sensitivity analysis are first selected based on the physical characteristics and model structure. Both regression coefficients and standardized regression coefficients for the selected independent variables are calculated using the results from sampling‐based Monte Carlo simulations. Results illustrate that, while as many as 630 independent variables potentially contribute to the calculation of the total annual ground‐water discharge for the case study area, a selection of seven independent variables could be used to develop an accurate regression model, accounting for more than 96% of the total variance in ground‐water discharge. Results indicate that the variability of ET rate for moderately dense desert shrubland contributes to about 75% of the variance in the total ground‐water discharge estimates. These results point to a need to better quantify ET rates for moderately dense shrubland to reduce overall uncertainty in estimates of ground‐water discharge. While the approach proposed here uses a basic ground‐water discharge model taken from an earlier study, the procedure of quantifying uncertainty and sensitivity can be generalized to handle other types of environmental models involving large numbers of independent variables.     

Mid‐Range Streamflow Forecasts Based on Climate Modeling – Statistical Correction and Evaluation1

Abstract: Mid‐range streamflow predictions are extremely important for managing water resources. The ability to provide mid‐range (three to six months) streamflow forecasts enables considerable improvements in water resources system operations. The skill and economic value of such forecasts are of great interest. In this research, output from a general circulation model (GCM) is used to generate hydrologic input for mid‐range streamflow forecasts. Statistical procedures including: (1) transformation, (2) correction, (3) observation of ensemble average, (4) improvement of forecast, and (5) forecast skill test are conducted to minimize the error associated with different spatial resolution between the large‐scale GCM and the finer‐scale hydrologic model and to improve forecast skills. The accuracy of a streamflow forecast generated using a hydrologic model forced with GCM output for the basin was evaluated by forecast skill scores associated with the set of streamflow forecast values in a categorical forecast. Despite the generally low forecast skill score exhibited by the climate forecasting approach, precipitation forecast skill clearly improves when a conditional forecast is performed during the East Asia summer monsoon, June through August.     

Assessment of the Hydrogeochemistry and Groundwater Quality of the Tarim River Basin in an Extreme Arid Region, NW China

The concentrations of the major and trace elements in the groundwater of the Tarim River Basin (TRB), the largest inland river basin of China, were analyzed before and during rainy seasons to determine the hydrogeochemistry and to assess the groundwater quality for irrigation and drinking purposes. The groundwater within the TRB was slightly alkaline and characterized by high ionic concentrations. The groundwater in the northern sub-basin was fresh water with a Ca²⁺–HCO₃ ^? water type, whereas the groundwater in the southern and central sub-basins was brackish with a Na⁺–Cl^? water type. Evaporite dissolution and carbonate weathering were the primary and secondary sources of solutes in the groundwater within the basin, whereas silicate weathering played a minor role. The sodium adsorption ratio (SAR), water quality index (WQI), and sodium percentage (%Na) indicated that the groundwater in the northern sub-basin was suitable for irrigation and drinking, but that in the southern and central sub-basins was not suitable. The groundwater quality was slightly better in the wet season than in the dry season. The groundwater could be used for drinking after treatment for B³⁺, F^?, and SO₄ ^2? and for irrigation after control of the sodium and salinity hazards. Considering the high corrosivity ratio of the groundwater in this area, noncorrosive pipes should be used for the groundwater supply. For sustainable development, integrated management of the surface water and the groundwater is needed in the future.     

Streamflow,Sediment Transport,and Geomorphic Change during the 2011 Flood on the Missouri River Near Bismarck–Mandan,ND

Geomorphic change from extreme events in large managed rivers has implications for river management. A steady‐state, quasi‐three‐dimensional hydrodynamic model was applied to a 29‐km reach of the Missouri River using 2011 flood data. Model results for an extreme flow (500‐year recurrence interval [RI]) and an elevated managed flow (75‐year RI) were used to assess sediment mobility through examination of the spatial distribution of boundary or bed shear stress (τ_b) and longitudinal patterns of average τ_b, velocity, and kurtosis of τ_b. Kurtosis of τ_b was used as an indicator of planform channel complexity and can be applied to other river systems. From differences in longitudinal patterns of sediment mobility for the two flows we can infer: (1) under extreme flow, the channel behaves as a single‐thread channel controlled primarily by flow, which enhances the meander pattern; (2) under elevated managed flows, the channel behaves as multithread channel controlled by the interaction of flow with bed and channel topography, resulting in a more complex channel; and (3) for both flows, the model reach lacks a consistent pattern of deposition or erosion, which indicates migration of areas of erosion and deposition within the reach. Despite caveats and limitations, the analysis provides useful information about geomorphic change under extreme flow and potential implications for river management. Although a 500‐year RI is rare, extreme hydrologic events such as this are predicted to increase in frequency.     

Long‐Term Trends in Streamflow and Precipitation in Northwest California and Southwest Oregon, 1953‐2012

Using nonparametric Mann‐Kendall tests, we assessed long‐term (1953‐2012) trends in streamflow and precipitation in Northern California and Southern Oregon at 26 sites regulated by dams and 41 “unregulated” sites. Few (9%) sites had significant decreasing trends in annual precipitation, but September precipitation declined at 70% of sites. Site characteristics such as runoff type (groundwater, snow, or rain) and dam regulation influenced streamflow trends. Decreasing streamflow trends outnumbered increasing trends for most months except at regulated sites for May‐September. Summer (July‐September) streamflow declined at many sites, including 73% of unregulated sites in September. Applying a LOESS regression model of antecedent precipitation vs. average monthly streamflow, we evaluated the underlying streamflow trend caused by factors other than precipitation. Decreasing trends in precipitation‐adjusted streamflow substantially outnumbered increasing trends for most months. As with streamflow, groundwater‐dominated sites had a greater percent of declining trends in precipitation‐adjusted streamflow than other runoff types. The most pristine surface‐runoff‐dominated watersheds within the study area showed no decreases in precipitation‐adjusted streamflow during the summer months. These results suggest that streamflow decreases at other sites were likely due to more increased human withdrawals and vegetation changes than to climate factors other than precipitation quantity.     

Effects of Rainfall and Ground‐Water Pumping on Streamflow in Mākaha,O’ahu,Hawai’i1

Abstract: Land‐use/land‐cover changes in Mākaha valley have included the development of agriculture, residential dwellings, golf courses, potable water supply facilities, and the introduction of alien species. The impact of these changes on surface water and ground water resources in the valley is of concern. In this study, streamflow, rainfall, and ground‐water pumping data for the upper part of the Mākaha valley watershed were evaluated to identify corresponding trends and relationships. The results of this study indicate that streamflow declined during the ground‐water pumping period. Mean and median annual streamflow have declined by 42% (135 mm) and 56% (175 mm), respectively, and the mean number of dry stream days per year has increased from 8 to 125. Rainfall across the study area appears to have also declined though it is not clear whether the reduction in rainfall is responsible for all or part of the observed streamflow decline. Mean annual rainfall at one location in the study area declined by 14% (179 mm) and increased by 2% (48 mm) at a second location. Further study is needed to assess the effect of ground‐water pumping and to characterize the hydrologic cycle with respect to rainfall, infiltration, ground‐water recharge and flow in the study area, and stream base flow and storm flow.     

Development and Operational Testing of a Super‐Ensemble Artificial Intelligence Flood‐Forecast Model for a Pacific Northwest River

Coastal catchments in British Columbia, Canada, experience a complex mixture of rainfall‐ and snowmelt‐driven contributions to flood events. Few operational flood‐forecast models are available in the region. Here, we integrated a number of proven technologies in a novel way to produce a super‐ensemble forecast system for the Englishman River, a flood‐prone stream on Vancouver Island. This three‐day‐ahead modeling system utilizes up to 42 numerical weather prediction model outputs from the North American Ensemble Forecast System, combined with six artificial neural network‐based streamflow models representing various slightly different system conceptualizations, all of which were trained exclusively on historical high‐flow data. As such, the system combines relatively low model development times and costs with the generation of fully probabilistic forecasts reflecting uncertainty in the simulation of both atmospheric and terrestrial hydrologic dynamics. Results from operational testing by British Columbia's flood forecasting agency during the 2013‐2014 storm season suggest that the prediction system is operationally useful and robust.     

Temporal‐spatial variations of air pollutants in Lanzhou,Gansu Province,China, during the spring–summer periods, 2014–2016

In this article, we analyzed the mass concentrations of particulate matter 2.5 micrometers (µm) or less in size (PM_2.5), particulate matter 10 µm or less in size (PM₁₀), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), carbon monoxide (CO), and ozone (O₃) in Lanzhou, the capital of Gansu province, China. We analyzed monitoring data collected from five air quality monitoring stations during the spring–summer period from 2014 to 2016. Our comparison of contaminant concentrations and average diurnal, daily, monthly, and annual concentrations revealed that the average concentrations of PM_2.5 and PM₁₀ amounted to 128.57 and 46.4 micrograms per cubic meters (µg/m³), respectively, exceeding the Chinese National Ambient Air Quality Standard (NAAQS). We used the Pearson correlation coefficient to establish connections between particulate matter and gaseous pollutants. The results show significant differences in the concentration levels of airborne pollutants. The Pearson correlation coefficient between PM_2.5 and PM₁₀ had the highest coefficient of r = 0.842. A correlation between the two particulate matter sizes (PM_2.5 and PM₁₀) and SO₂ was PM_2.5 and SO₂ r = 0.313; PM₁₀ and SO₂ r = 0.279; and CO and the two particulate matter sizes, PM_2.5 and CO r = 0.304; and PM₁₀ and CO r = 0.203. The average monthly ratio for the study months of PM_2.5 to PM₁₀ was 0.361. In addition, we used the hybrid single particle Lagrangian integrated trajectory model for tracking sources and pathways of the air pollutants in Lanzhou.     

Geospatial and Temporal Analysis of a 20‐Year Record of Landsat‐Based Water Clarity in Minnesota's 10,000 Lakes

A large 20‐year database on water clarity for all Minnesota lakes ≥8 ha was analyzed statistically for spatial distributions, temporal trends, and relationships with in‐lake and watershed factors that potentially affect lake clarity. The database includes Landsat‐based water clarity estimates expressed in terms of Secchi depth (SD_Landsat), an integrative measure of water quality, for more than 10,500 lakes for time periods centered around 1985, 1990, 1995, 2000, and 2005. Minnesota lake clarity is lower (more turbid) in the south and southwest and clearer in the north and northeast; this pattern is evident at the levels of individual lakes and ecoregions. Temporal trends in clarity were detected in ~11% of the lakes: 4.6% had improving clarity and 6.2% had decreasing clarity. Ecoregions in southern and western Minnesota, where agriculture is the predominant land use, had higher percentages of lakes with decreasing clarity than the rest of the state, and small and shallow lakes had higher percentages of decreasing clarity trends than large and deep lakes. The mean SD_Landsat statewide remained stable from 1985 to 2005 but decreased in ecoregions dominated by agricultural land use. Deep lakes had higher clarity than shallow lakes statewide and for lakes grouped by land cover. SD_Landsat decreased as the percentage of agriculture and/or urban area increased at county and catchment levels and it increased with increasing forested land.     

Impact of Temporal Resolution of Flow‐Duration Curve on Sediment Load Estimation1

Chen, Li, Rina Schumer, Anna Knust, and William Forsee, 2011. Impact of Temporal Resolution of Flow‐Duration Curve on Sediment Load Estimation. Journal of the American Water Resources Association (JAWRA) 48(1): 145‐155. DOI: 10.1111/j.1752‐1688.2011.00602.x Abstract: Estimates of a channel’s annual sediment transport capacity typically incorporate annualized flow‐duration curves. Average daily flow data, commonly used to develop flow‐duration curves, may not adequately describe sediment‐transporting flows in arid and semiarid ephemeral streams. In this study, we examined impacts of varied temporal resolution flow data on annual sediment load estimation. We derived flow‐duration curves for eight sites in the Southwestern United States based on both 15‐min and daily‐averaged flow data. We then estimated sediment loads for both flow‐duration curves using the Sediment Impact Analysis Method, implemented in HEC‐RAS. When average daily flow is used to generate flow‐duration curves, sediment load estimation is lower by up to an order of magnitude. This trend is generally unaffected by uncertainty associated with sediment particle size or hydraulic roughness. The ratio of sediment loads estimated by 15‐min versus daily‐averaged flow‐duration curves is strongly correlated with channel slope, being greater on steep‐slope channels. Sediment loads estimated by the two types of flow‐duration curves are closely correlated, suggesting possible relationships for improving predictions when high‐temporal resolution data are unavailable. Results also suggest that the largest flow contributes significantly to total sediment load, and thus will greatly impact ephemeral stream geomorphology in arid and semiarid regions.     

Streamflow Changes in the South Atlantic,United States During the Mid‐ and Late 20th Century1

Abstract: Repeated severe droughts over the last decade in the South Atlantic have raised concern that streamflow may be systematically decreasing, possibly due to climate variability. We examined the monthly and annual trends of streamflow, precipitation, and temperature in the South Atlantic for the time periods: 1934‐2005, 1934‐1969, and 1970‐2005. Streamflow and climate (temperature and precipitation) trends transitioned ca. 1970. From 1934 to 1969, streamflow and precipitation increased in southern regions and decreased in northern regions; temperature decreased throughout the South Atlantic. From 1970 to 2005, streamflow decreased, precipitation decreased, and temperature increased throughout the South Atlantic. It is unclear whether these will be continuing trends or simply part of a long‐term climatic oscillation. Whether these streamflow trends have been driven by climatic or anthropogenic changes, water resources management faces challenging prospects to adapt to decadal‐scale persistently wet and dry hydrologic conditions.