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.     

Trends in Western U.S. Snowpack and Related Upper Colorado River Basin Streamflow1

Miller, W. Paul and Thomas C. Piechota, 2011. Trends in Western U.S. Snowpack and Related Upper Colorado River Basin Streamflow. Journal of the American Water Resources Association (JAWRA) 47(6):1197–1210. DOI: 10.1111/j.1752‐1688.2011.00565.x Abstract: Water resource managers in the Western United States (U.S.) are currently faced with the challenge of adapting to unprecedented drought and uncertain impacts of climate change. Recent research has indicated increasing regional temperature and changes to precipitation and streamflow characteristics throughout the Western U.S. As such, there is increased uncertainty in hydroclimatological forecasts, which impact reservoir operations and water availability throughout the Western U.S., particularly in the Colorado River Basin. Previous research by the authors hypothesized a change in the character of precipitation (i.e., the frequency and amount of rainfall and snowfall events) throughout the Colorado River Basin. In the current study, 398 snowpack telemetry stations were investigated for trends in cumulative precipitation, snow water equivalent, and precipitation events. Observations of snow water equivalent characteristics were compared to observations in streamflow characteristics. Results indicate that the timing of the last day of the snow season corresponds well to the volume of runoff observed over the traditional peak flow season (April through July); conversely, the timing of the first day of the snow season does not correspond well to the volume of runoff observed over the peak flow season. This is significant to water resource managers and river forecasters, as snowpack characteristics may be indicative of a productive or unproductive runoff season.     

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.     

THE EFFECTS OF CLIMATE CHANGE AND IRRIGATION ON CRITERION LOW STREAMFLOWS USED FOR DETERMINING TOTAL MAXIMUM DAILY LOADS1

ABSTRACT: This paper addresses the possible impacts of global climate change on low streamflows in the Midwest, both directly, through lower precipitation, and indirectly, by rendering irrigation profitable in areas where it has found little application in the past. In the analysis presented here, streamflow data are altered to represent the effect of climate change and stream-supplied irrigation, and then used to estimate new values for two low-flow criteria, the one- and seven-day-ten-year low flows (₇Q₁₀ and ₁Q₁₀) under 20 climate change and irrigation scenarios. Additionally, the frequencies of violation of these two criteria, and multiple violations in a three-year period, are determined. Results show that the potential impact of the assumed climate change scenarios on low flow standards is substantial. A 25 percent decrease in mean precipitation results in a 63 percent reduction in design flow, even in the absence of irrigation. With irrigation, the reduction can be as much as 100 percent. The frequency of single violations of low flow criteria is found to increase several fold with irrigation. The frequency of multiple violations of low flow criteria in a three-year period is sensitive to climate change, increasing from around 20 percent to nearly 100 percent as the climate change becomes more severe.     

VARIATIONS IN NORTHERN SIERRA NEVADA STREAMFLOW: IMPLICATIONS OF CLIMATE CHANGE1

ABSTRACT: Historical records of streamflow for an eastward- and a westward-draining stream in the northern Sierra Nevada have been analyzed for evidence of changes in runoff characteristics and patterns of variability. A trend of increasing and more variable winter streamflow began in the mid-1960s. Mean monthly streaniflow during December through March was substantially greater for water years 1965–1990 compared to water years 1939–1964. Increased winter and early-spring streamflow during the later period is attributed to small increases in temperature, which increase the rain-to-snow ratio at lower altitudes and cause the snowpack to melt earlier in the season at higher altitudes. The timing of snowmelt runoff on the western slope of the Sierra Nevada is more sensitive than it is on the eastern slope to changes in temperature, owing to predominantly lower altitudes on the west side. This difference in sensitivity suggests that basins on the east side of the Sierra Nevada have a more reliable water supply (as snow storage) than western-slope basins during warming trends.     

USE OF CLIMATE PREDICTIONS TO DECIDE A WATER MANAGEMENT PROBLEM1

ABSTRACT: Seasonal precipitation predictions were utilized in a water management decision with major economic, societal, and political ramifications. A summer (1984) drought had created a situation calling for possible fall season use of state waters from two major multipurpose reservoirs with an ensuing effect on water price negotiations. Choices facing management and use of water from the reservoirs were to invoke expensive water restrictions with a 33 percent chance of being right, do nothing (66 percent chance of wrong outcome), or use the precipitation predictors (for above normal fall rain) having a 50 percent chance of error. Hydrologists chose to follow the precipitation predictions, which proved to be accurate for the fall of 1984, helping to reveal the long-term value of using well understood climate predictions in water management.