Prediction of Streamflow Regime and Annual Runoff for Ungauged Basins Using a Distributed Monthly Water Balance Model1

Moore, R.D. (Dan), J.W. Trubilowicz, and J.M. Buttle, 2011. Prediction of Streamflow Regime and Annual Runoff for Ungauged Basins Using a Distributed Monthly Water Balance Model. Journal of the American Water Resources Association (JAWRA) 48(1): 32‐42. DOI: 10.1111/j.1752‐1688.2011.00595.x Abstract: Prediction of streamflow in ungauged basins is a global challenge, but is particularly an issue in physiographically complex regions like British Columbia (BC), Canada. The objective of this study was to assess the accuracy of a simple water balance model that can be run using existing spatial datasets. The model was developed by modifying an existing monthly water balance model to account for interception loss from forest canopy, glacier melt, and evaporation from lakes. The model was run using monthly climate normals from the ClimateBC application, which have a horizontal resolution of 400 m. Each ClimateBC grid cell was classified as forest, open land, glacier or water surface based on provincial scale digital maps of biogeoclimatic zones, glaciers, and water. The output was monthly mean runoff from each grid cell. These values were integrated within the catchment boundaries for streams gauged by the Water Survey of Canada. Annual runoff was predicted with modest accuracy: after updating the predicted runoff by interpolating errors from neighboring gauged streams, the mean absolute error was 25.4% of the gauged value, and 52% of the streams had errors less than 20%. However, the model appears to be quite robust in distinguishing between pluvial, hybrid, and melt‐dominated hydroclimatic regimes, and therefore has promise as a tool for catchment classification.     

Reducing Streamflow Forecast Uncertainty: Application and Qualitative Assessment of the Upper Klamath River Basin,Oregon1

Abstract: The accuracy of streamflow forecasts depends on the uncertainty associated with future weather and the accuracy of the hydrologic model that is used to produce the forecasts. We present a method for streamflow forecasting where hydrologic model parameters are selected based on the climate state. Parameter sets for a hydrologic model are conditioned on an atmospheric pressure index defined using mean November through February (NDJF) 700‐hectoPascal geopotential heights over northwestern North America [Pressure Index from Geopotential heights (PIG)]. The hydrologic model is applied in the Sprague River basin (SRB), a snowmelt‐dominated basin located in the Upper Klamath basin in Oregon. In the SRB, the majority of streamflow occurs during March through May (MAM). Water years (WYs) 1980‐2004 were divided into three groups based on their respective PIG values (high, medium, and low PIG). Low (high) PIG years tend to have higher (lower) than average MAM streamflow. Four parameter sets were calibrated for the SRB, each using a different set of WYs. The initial set used WYs 1995‐2004 and the remaining three used WYs defined as high‐, medium‐, and low‐PIG years. Two sets of March, April, and May streamflow volume forecasts were made using Ensemble Streamflow Prediction (ESP). The first set of ESP simulations used the initial parameter set. Because the PIG is defined using NDJF pressure heights, forecasts starting in March can be made using the PIG parameter set that corresponds with the year being forecasted. The second set of ESP simulations used the parameter set associated with the given PIG year. Comparison of the ESP sets indicates that more accuracy and less variability in volume forecasts may be possible when the ESP is conditioned using the PIG. This is especially true during the high‐PIG years (low‐flow years).     

Long‐Term Streamflow Response to Climatic Variability in the Loess Plateau,China1

Abstract: The Loess Plateau region in northwestern China has experienced severe water resource shortages due to the combined impacts of climate and land use changes and water resource exploitation during the past decades. This study was designed to examine the impacts of climatic variability on streamflow characteristics of a 12‐km² watershed near Tianshui City, Gansu Province in northwestern China. Statistic analytical methods including Kendall’s trend test and stepwise regression were used to detect trends in relationship between observed streamflow and climatic variables. Sensitivity analysis based on an evapotranspiration model was used to detect quantitative hydrologic sensitivity to climatic variability. We found that precipitation (P), potential evapotranspiration (PET) and streamflow (Q) were not statistically significantly different (p > 0.05) over the study period between 1982 and 2003. Stepwise regression and sensitivity analysis all indicated that P was more influential than PET in affecting annual streamflow, but the similar relationship existed at the monthly scale. The sensitivity of streamflow response to variations of P and PET increased slightly with the increase in watershed dryness (PET/P) as well as the increase in runoff ratio (Q/P). This study concluded that future changes in climate, precipitation in particular, will significantly impact water resources in the Loess Plateau region an area that is already experiencing a decreasing trend in water yield.     

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.     

连续流动分析法测定水中总氮的不确定度评定

在实验室分析基础上,对连续流动分析法测定水中总氮过程的不确定度进行评定。本文建立了数学模型,对不确定度来源进行了分析,并计算了不确定度分量、合成不确定度及扩展不确定度,最后给出了总氮测量结果的标准表示方法。     

Characterizing Runoff and Water Yield for Headwater Catchments in the Southern Sierra Nevada

In a Mediterranean climate where much of the precipitation falls during winter, snowpacks serve as the primary source of dry season runoff. Increased warming has led to significant changes in hydrology of the western United States. An important question in this context is how to best manage forested catchments for water and other ecosystem services? Answering this basic question requires detailed understanding of hydrologic functioning of these catchments. Here, we depict the differences in hydrologic response of 10 catchments. Size of the study catchments ranges from 50 to 475 ha, and they span between 1,782 and 2,373 m elevation in the rain‐snow transitional zone. Mean annual streamflow ranged from 281 to 408 mm in the low elevation Providence and 436 to 656 mm in the high elevation Bull catchments, resulting in a 49 mm streamflow increase per 100 m (R² = 0.79) elevation gain, despite similar precipitation across the 10 catchments. Although high elevation Bull catchments received significantly more precipitation as snow and thus experienced a delayed melt, this increase in streamflow with elevation was mainly due to a reduction in evapotranspiration (ET) with elevation (45 mm/100 m, R² = 0.65). The reduction in ET was attributed to decline in vegetation density, growing season, and atmospheric demand with increasing elevation. These findings suggest changes in streamflow in response to climate warming may likely depend on how vegetation responds to those changes in climate.     

Uncertainty characterization approaches for risk assessment of DBPs in drinking water: A review

The management of risk from disinfection by-products (DBPs) in drinking water has become a critical issue over the last three decades. The areas of concern for risk management studies include (i) human health risk from DBPs, (ii) disinfection performance, (iii) technical feasibility (maintenance, management and operation) of treatment and disinfection approaches, and (iv) cost. Human health risk assessment is typically considered to be the most important phase of the risk-based decision-making or risk management studies. The factors associated with health risk assessment and other attributes are generally prone to considerable uncertainty. Probabilistic and non-probabilistic approaches have both been employed to characterize uncertainties associated with risk assessment. The probabilistic approaches include sampling-based methods (typically Monte Carlo simulation and stratified sampling) and asymptotic (approximate) reliability analysis (first- and second-order reliability methods). Non-probabilistic approaches include interval analysis, fuzzy set theory and possibility theory. However, it is generally accepted that no single method is suitable for the entire spectrum of problems encountered in uncertainty analyses for risk assessment. Each method has its own set of advantages and limitations. In this paper, the feasibility and limitations of different uncertainty analysis approaches are outlined for risk management studies of drinking water supply systems. The findings assist in the selection of suitable approaches for uncertainty analysis in risk management studies associated with DBPs and human health risk.     

System Dynamics to Sustainable Water Resources Management in the Eastern Snake Plain Aquifer Under Water Supply Uncertainty1

Abstract: Water supply uncertainty continues to threaten the reliability of regional water resources in the western United States. Climate variability and water dispute potentials induce water managers to develop proactive adaptive management strategies to mitigate future hydroclimate impacts. The Eastern Snake Plain Aquifer in the state of Idaho is also facing these challenges in the sense that population growth and economic development strongly depend on reliable water resources from underground storage. Drought and subsequent water conflict often drive scientific research and political agendas because water resources availability and aquifer management for a sustainable rural economy are of great interest. In this study, a system dynamics approach is applied to address dynamically complex problems with management of the aquifer and associated surface‐water and groundwater interactions. Recharge and discharge dynamics within the aquifer system are coded in an environmental modeling framework to identify long‐term behavior of aquifer responses to uncertain future hydrological variability. The research shows that the system dynamics approach is a promising modeling tool to develop sustainable water resources planning and management in a collaborative decision‐making framework and also to provide useful insights and alternative opportunities for operational management, policy support, and participatory strategic planning to mitigate future hydroclimate impacts in human dimensions.     

Calibration and Uncertainty Analysis Using the Sparrow Model for Dissolved‐Solids Transport in the Upper Colorado River Basin

Salinity in the Upper Colorado River Basin (UCRB) is due to both natural sources and processes, and anthropogenic activities. Given economic damage due to salinity of $295 million in 2010, understanding salinity sources and production together with transport are of great importance. SPAtially Referenced Regressions On Watershed (SPARROW) is a nonlinear regression water quality model that simulates sources and transport of contaminants such as dissolved‐solids. However, SPARROW simulations of dissolved‐solids in the UCRB only represent conditions through 1998 due to limited data availability. More importantly, prior simulations focused on a single year calibration and its transferability to other years, and the validity of this approach is questionable, given the changing hydrologic and climatic conditions. This study presents different calibration approaches to assess the best approach for reducing model uncertainty. This study conducted simulations from 1999 to 2011, and the results showed good model accuracy. However, the number of monitoring stations decreased significantly in recent years resulting in higher model uncertainty. The uncertainty analysis was conducted using SPARROW results and bootstrapping. The results suggest that the watershed rankings based on salinity yields changed due to the uncertainty analysis and therefore, uncertainty consideration should be an important part of the management strategy.     

Stochastic Watershed Water Quality Simulation for TMDL Development – A Case Study in the Newport Bay Watershed1

Abstract: Systematic consideration of uncertainty in data, model structure, and other factors is generally unaddressed in most Total Maximum Daily Load (TMDL) calculations. Our previous studies developed the Management Objectives Constrained Analysis of Uncertainty (MOCAU) approach as an uncertainty analysis technique specifically for watershed water quality models, based on a synthetic case. In this study, we applied MOCAU to analyze diazinon loading in the Newport Bay watershed (Southern California). The study objectives included (1) demonstrating the value of performing stochastic simulation and uncertainty analysis for TMDL development, using MOCAU as the technique and (2) evaluating the existing diazinon TMDL and generating insights for the development of scientifically sound TMDLs, considering uncertainty. The Watershed Analysis Risk Management Framework model was used as an example of a complex watershed model. The study revealed the importance and feasibility of conducting stochastic watershed water quality simulation for TMDL development. The critical role of management objectives in a systematic uncertainty assessment was well demonstrated. The results of this study are intuitive to TMDL calculation, model structure improvement and sampling strategy design.