H43A-0954
Collaborative Modeling in New Mexico's Upper Gila and San Francisco River Basin
The 2005 Arizona Water Settlements Act (AWSA) has given southwestern New Mexico a unique opportunity to appropriate water from the Upper Gila River basin. This appropriation calls for Arizona irrigators to "trade" their existing use of Gila River water for Central Arizona Project water to realize New Mexico's legal right to develop water originating in its portion of the Upper Gila River watershed. The complexity of the AWSA and various stakeholders interested in the implications of the settlement has led to the development of a collaborative modeling team. As a team member, Sandia National Laboratories is tasked with building an integrated basin scale system-dynamics model that can implement the constraints outlined in the AWSA by projecting water supply and demand scenarios into the future. By building this model, stakeholders will gain insight into the hydrologic complexities inherent in a river basin, and it will allow them to evaluate whether alternate water use scenarios will be allowed under the constraints outlined by the AWSA. The model replicates historic surface and ground water conditions in the basin using available data for supply, including gauges that measure stream flow, ditch flow, and precipitation. Demands are measured through annual hydrographic survey records for agricultural production, industrial water use by mining, municipal and domestic use in both urban and rural communities, and riparian evapotranspiration. Within the system-dynamics framework, volumetric flow of water is the dynamic state variable calculated from one river reach to the next. Stream gauge, climate and consumptive use data are used to calibrate the historic baseline flows. There is a great deal of uncertainty that must be addressed when attempting to model a large basin. Integrating a watershed model to add the contribution of ungauged tributaries is part of this effort. Another challenge is the presence of federally listed endangered avian and aquatic species whose flow regime requirements are not well understood. Population growth within the basin is an issue that must also be addressed as well as demands from large municipalities located outside of the basin. In addition, climate change and variability can alter the type of and timing of precipitation from one year to the next. To address these uncertainties, team members are given a variety of options ranging from setting future climate and flow conditions, the ability to define critical reaches and set minimum flows for riparian health, ranges for population growth rates, and options for moving water from one use to another. The team will then come up with a prioritized set of model "scenarios" that it anticipates for the future. The predictive dynamic responses due to different scenarios can be assessed relative to their baseline values to enhance our understanding of water balances in the region. Sandia is a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin Company, for the United States Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.
H43A-0955
Analysis of precipitable water vapor and liquid water path by microwave radiometer during 2001 – 2002
Based on the observation of the Microwave Radiometer (MWR, WVR-1100) at Cheongju and Hapcheon in South Korea, the precipitable water vapor (PWV) and liquid water path (LWP) have been analyzed. Comparison of the PWVs measured by MWR at Cheongju and Hapcheon gives good agreement above the 0.9 of correlation coefficient with that of radiosonde at the two nearest sites (Osan and Gwangju), respectively. The PWVs show the seasonality, but do not the regional characteristics evidently. The LWP shows not only the seasonality but also regional difference. These regional characteristics seem come from the regional different solar radiation.
H43A-0956
Sources of Seasonal Water-Supply Forecast Skill in the Western US
Many water supplies in the western US depend on water that is stored in snowpacks and reservoirs during the cool, wet seasons for release and use in the following warm seasons. Managers of these water supplies must decide each winter how much water will be available in subsequent seasons so that they can proactively capture and store water and can make reliable commitments for later deliveries. Long-lead water-supply forecasts are thus important components of water managers' decisionmaking. Present-day operational water-supply forecasts draw skill from observations of the amount of water in upland snowpacks, along with estimates of the amount of water otherwise available (often via surrogates for antecedent precipitation, soil moisture or baseflows). Occasionally, the historical hydroclimatic influences of various global climate conditions may be factored in to forecasts. The relative contributions of (potential) forecast skill for January-March and April-July seasonal water- supply availability from these sources are mapped across the western US as lag correlations among elements of the inputs and outputs from a physically based, regional land-surface hydrology model of the western US from 1950-1999. Information about snow-water contents is the most valuable predictor for forecasts made through much of the cool-season but, before the snows begin to fall, indices of El Nino-Southern Oscillation are the primary source of whatever meager skill is available. The contributions to forecast skill made available by knowledge of antecedent flows (a traditional predictor) and soil moisture at the time the long-lead forecast is issued are compared, to gain insights into the potential usefulness of new soil-moisture monitoring options in the region. When similar computations are applied to simulated flows under historical conditions, but with a uniform +2°C warming imposed, the widespread diminution of snowpacks reduces forecast skills, although skill contributed by measures of antecedent moisture conditions (soil moisture or baseflows) grow in stature, relative to snowpacks, in partial compensation. Forecast skills, e.g., of March forecasts for April-July water supplies from those parts of the region that yield the majority of the runoff, decline by an average of about 15% of captured variance in response to the imposed warming.
H43A-0957
Glacial Change in the Wind River Range, Wyoming, USA
The upper Green River Basin (GRB) [located in the upper Colorado River Basin] and the upper Wind-Bighorn River Basin (WBRB) [located in the upper Missouri-Mississippi River Basin] are separated by the Wind River Range (WRR) of Wyoming. The WRR is an unbroken 160-kilometer barrier in west central Wyoming that is host to 63 glaciers, the largest concentration of glaciers in the American Rocky Mountains. These glaciers serve as natural water reservoirs and the continued recession of glaciers will impact agricultural water supply in the region. Previous research determined that the glaciers in the WRR contribute approximately 30% of the total streamflow volume during the critical late summer / early fall growing season. However, the previous research was limited in scope to a small number of climatic stations and limited streamflow measurements. The proposed research improves on previous research by evaluating glacial recession in the WRR using remote sensing techniques. Glacier area and terminus position for 42 glacial complexes in the WRR (from 1985 to present) will be evaluated using LANDSAT Imagery and GIS techniques. Next, for selected glaciers, aerial photograph stereopairs will also be obtained from the USGS Earth Resources, Observation and Science (EROS) Data Center in Sioux Falls, South Dakota from 1966 to present. The stereopair images will be utilized to derive the surface elevation of glaciers and calculate volume change. Traditional methods require the user to view the two photos with a stereoscope to view an object in three dimensions. Modern techniques allow this process to be completed digitally. Leica Photogrammetry suite is used to specify the spatial coordinates of each photo and create a block file, a file that consists of two or more photographs of the same area that contain spatial coordinates of each photo. Once the block file is created, the user can view the objects contained in the overlapping portions of the photos and make vertical measurements. This process allows the user to calculate changes in surface area and changes in elevation, thus volume changes can be computed. Glacier volume will also be estimated from glacier surface areas using the Bahr et al. (1997) area-volume scaling method. Finally, field data (real-time differential GPS surface survey, ground penetrating radar of ice thickness and repeat photography) from a summer 2006 site visit to Dinwoody Glacier (located on the east slope of the WRR) will be compared to previous site visits in the past 40 years. The field data will either confirm or reject observations from the remote sensing approach.
H43A-0958
Probabilistic Long-Term Reservoir Storage Forecasting Using Multi-Objective Genetic Algorithms
In this study, the implicit stochastic optimization approach is used, and instead of using regression analysis for the optimization results, the developed reservoir operating rule is found directly from the optimization model. The piecewise-linear operating rule for the Soyanggang reservoir was developed using a multiobjective genetic algorithm (NSGA-II) and the synthetic inflow that was generated by time series modeling. In order to formulate the operating rule effectively, two aspects of the piecewise-linear operating rule are examined in detail: search space determination and effects of inflow and constraints. First, the upper and lower limits of the first and last end points are determined by frequency analysis. If the upper and lower limits are simply set to the storage values corresponding to normal pool and low water levels, respectively, the search space of NSGA-II would become very large, particularly for the non-flood season. Therefore, each quantile having 1% exceedance and nonexceedance probabilities is computed by the frequency analysis of the historical storage record on the first day of a month; these quantities are used as the upper and lower limits of the optimization model. Furthermore, these limits could be reasonable estimations with slight variations from the historical maximum and minimum values. In the case study, the simulation results are obtained by using the developed piecewise-linear operating rule. Four- and five-segmented operating rules are adopted along with six years of historical inflow data of the Soyanggang reservoir. The reservoir operation results show that the developed piecewise-linear operating rule can handle various inflow series that have different characteristics and can generally satisfy the constraints defined in the optimization model including the constraint of terminal storage. In addition, a probabilistic long- term reservoir storage forecast is provided. This storage forecast would be useful information since a system operator is able to evaluate the current status of the reservoir quantitatively, but not qualitatively.
H43A-0959
Uncertainty Assessment in Long-lead Drought Prediction Using GCMs Outputs
Drought is one of the major hazards that could cause excessive damages especially in arid and semiarid regions. A study by international panel on climate changes (IPCC) showed that the frequency of drought is increasing because of climate change impact. In this study certain scenarios on climate change that are included in the outputs of the GCM models, are considered in order to evaluate climate change effects on the characteristics of future drought events. For this purpose, different indices that reflect different aspects of drought impacts are considered. These indices consider precipitation, water supply and soil moisture variations in the drought periods. These indices are integrated through a hybrid index that is calculated based on drought damages using Probabilistic Neural Network (PNN). The drought characteristics are then estimated using the proposed algorithm over a one hundred year time horizon that the GCM outputs are available. For evaluation of the uncertainties in the long lead drought prediction, one hundred ensemble data are generated using Statistical Down Scaling Model (SDSM). Uncertainty analysis has been done by fitting probability distribution function to the ensemble results of the drought characteristics prediction. A small basin located at the northwestern part of Iran is used as the case study. The results of this study can be utilized by decision makers in the region to decide on future development plans of the basin and for developing drought emergency plans.
H43A-0960
A Sustainable Early Warning System for Climate Change Impacts on Water Quality Management
In this era of rapid social and technological change leading to interesting life complexity and environmental displacement, both positive and negative effects among ecosystems call for a balance in which there are impacts by climate changes. Early warning systems for climate change impacts are necessary in order to allow society as a whole to properly and usefully assimilate the masses of new information and knowledge. Therefore, our research addresses to build up a sustainable early warning mechanism. The main goal is to mitigate the cumulative impacts on the environment of climate change and enhance adaptive capacities. An effective early warning system has been proven for protection. However, there is a problem that estimate future climate changes would be faced with high uncertainty. In general, take estimations for climate change impacts would use the data from General Circulation Models and take the analysis as the Intergovernmental Panel on Climate Change declared. We follow the course of the method for analyzing climate change impacts and attempt to accomplish the sustainable early warning system for water quality management. Climate changes impact not only on individual situation but on short-term variation and long-term gradually changes. This kind characteristic should adopt the suitable warning system for long-term formulation and short- term operation. To continue the on-going research of the long-term early warning system for climate change impacts on water quality management, the short-term early warning system is established by using local observation data for reappraising the warning issue. The combination of long-term and short-term system can provide more circumstantial details. In Taiwan, a number of studies have revealed that climate change impacts on water quality, especially in arid period, the concentration of biological oxygen demand may turn into worse. Rapid population growth would also inflict injury on its assimilative capacity to degenerate. To concern about those items, the sustainable early warning system is established and the initiative fall into the following categories: considering the implications for policies, applying adaptive strategies and informing the new climate changes. By setting up the framework of early warning system expectantly can defend stream area from impacts damaging and in sure the sustainable development.
H43A-0961
Assessment of Hydroclimatic Trends Over the Colorado River Basin
Recent studies by a broad range of governmental agencies, universities, and experts in the scientific community have begun to acknowledge and address issues regarding climate change and trends. Most of these studies have focused on global scale trends in hydroclimatic variables and long-term impacts of climate change. The impacts of climate change are particularly important in the Colorado River Basin to resource managers, and water users who depend upon the Colorado River to provide water for flood control, consumptive use, irrigation, environmental, recreational, and energy demands. In this study, trends in hydroclimatic variables such as temperature, precipitation, streamflow and snowpack over the Colorado River Basin are considered and their interdependency discussed. Impacts of observed trends on the operation of the Colorado River and affects on water users are assessed. In this study, early peak runoff corresponds to persistent increasing trends in temperature. Observed monthly streamflow rates are consistently decreasing between April and July, traditionally when peak flow is observed. The potential for incorporation of hydroclimatic trends into the improvement of forecasts is explored.
H43A-0962
Application of LDAS-era land surface models for drought characterization and prediction in Washington State
Accurate appraisal of the current and future status of drought is still a major challenge for scientists and water managers. No ubiquitous definition of drought exists and different indices of meteorological and hydrological elements yield different perspectives on drought. Although traditional drought indices are based on meteorological inputs, hydrologic variables such as soil moisture and runoff, the by-products of the hydro- meteorological process affecting a watershed, can be used to derive indicators of drought status, and are arguably more closely related to the societal impacts of drought than the drought indices based on the meteorological variables only. This presentation compares drought metrics based on modeled soil moisture and runoff with the conventional drought indices and other independent measures, including observed or naturalized streamflow and reservoir levels. Hydrologic fields used for this analysis are simulated by a physically- based, semi-distributed hydrologic model, the Variable Infiltration Capacity model, for Washington State We also show that ensemble hydrologic predictions of these fields can be used to extend both traditional and model- based drought indices into the future and provide uncertainty estimates for the future evolution of a drought. The significant similarities between the model-based metrics and the traditional indicators of drought suggest that the hydrologic models are at least as capable of characterizing drought as traditional meteorological indices, and offer a way forward toward developing a capacity for drought prediction. http://www.hydro.washington.edu/forecast/sarp/
H43A-0963
Improving Ensemble Streamflow Prediction Using Interdecadal/Interannual Climate Variability
An overview of a research project that investigates the ability to improve ensemble streamflow forecasts with improved understanding of interdecadal climate variability is presented. The research builds on new advances that researchers have found on the influence of interdecadal climate variability (i.e., Pacific Decadal Oscillation and Atlantic Monthly Oscillation) and Pacific sea surface temperatures on streamflow in the Colorado River Basin (Tootle et al., 2005, Tootle and Piechota, 2006). Ensemble hydrologic prediction, which explicitly addresses forecast uncertainty in terms of the outcome's occurrence probability, is a plausible and promising approach for developing a seamless suite of intraseasonal to interannual hydrometeorological predictions, one of the high priorities of the National Oceanic and Atmospheric Administration (NOAA) and specifically, the Climate Prediction Program for the Americas (CPPA). This new information will be combined with existing capabilities in the Ensemble Streamflow Prediction (ESP) system for the Colorado River Basin to produce improved long-range streamflow forecasts. Preliminary research is presented on how Colorado River streamflow is influenced during the different phases of ENSO, PDO, AMO and the coupled impacts.
H43A-0964
The Impacts of Climate Change on Hydrology and Water Resources in Zayandeh-Rood Basin - Iran
Increasing concentration of greenhouse gases may have significant consequences on the global climate. If climate change occurs, changes in temperature and precipitation may have profound impacts on hydrologic processes, water resources and water uses such as agriculture. In Zayandeh-River Basin of Iran, agriculture is an important economic activity and is the main water user. Climate change may exacerbate the already contentious water supply situation in the basin. This paper focuses on the impact of climate change on hydrology and water resources of Zayandeh-Rood river basin. GCM models do not have suitable spatial resolution for regional assessment, so GCM outputs should be downscaled to the regional scale. In this paper, statistical downscaling is used in two difference methods (probability and regression) for downscaling the CGCM2 model outputs under A2 and B2 scenarios for two periods: 2021-2050 (immediate future) and 2071-2100 (far future). Temperature and precipitation projections from the downscaled GCM outputs were used as inputs to the hydrologic model. To study the impact of climate change on the water resources in the basin, an operational model was used to simulate the operation of the Zayandeh-Rood reservoir under different hydrologic projections. Both scenarios showed similar increases in temperature while they have less agreement in the amount and rate of precipitation they projected. The results of this study also show that the water resources in the study area are sensitive to changes in temperature and precipitation projections. The reservoir simulations provide information on the timing and rate of changes expected in water supply. The methodology developed can be used to predict the impacts of new or updated predictions of climate change. Vulnerability to climate change may be characterized as a function of three components: sensitivity, exposure, and adaptive capacity. In this study, only the first component and infrastructure as an indicator of adaptive capacity were considered. To assess the true vulnerability, other components and factors should be considered as well.
H43A-0965
The Impacts of Climate Change and Variability on Water Resources in a Semiarid Region in Mexico: The Rio Yaqui-Basin.
This work consists of determining the impacts of climate change and variability on precipitation and reservoir storage in the Yaqui Basin. The basin is classified as a semi-arid climate with an average rainfall of 527 mm per year. It consists of roughly 72,000 square kilometers of land, primarily in northwest Mexico. The water to meet all demands comes from three reservoirs in series constructed along the river. Agriculture is the main user of water in the basin. A rainfall-runoff model has been created and calibrated and integrated into a node link network that includes reservoir storage and extractions by users. Precipitation data was interpolated on a monthly basis over a thirty three year time span with data collected from weather stations throughout the basin. Distributions of static runoff coefficients were generated based on published regional maps. Using GIS the product of the precipitation and runoff coefficients were determined and a monthly hypothetical runoff was calculated. This monthly runoff data was merged into three seasons. This GIS based seasonal runoff was further adjusted by calibrating it against thirty three years of seasonal inflow data collected at each reservoir. The calibration is done by fitting a linear model relating the GIS based runoff with the reservoir inflows. Three different approaches for generating future precipitation scenarios based on a 30-year planning period were applied. The first approach involved repeating the 1970-2000 historical precipitation record. The second approach involved time-series analysis of the 1970-2000 record, developing a temporally-correlated precipitation model, and then applying the precipitation model for future predictions. The third approach involves adjusting the 1970-2000 historical precipitation using outputs from global climate models. Several climate model-climate scenarios were included in this approach. The sensitivity of available reservoir storage to each of the future precipitation scenarios is assessed. The effects of various sources of uncertainty, such as uncertainty in rainfall- runoff model predictions, also are assessed.
H43A-0966
Sustainable Stream Waste Load Allocation with Considering Equity
The stream assimilative capacity is the carrying capacity of a river for the maximum waste load without exceeding the water quality standard. However, only optimizing maximal waste loads may lead to inequity. Equity is an important issue in waste load allocation problems. This research formulates a multi-objective model that considers minimizing inequity and maximizing total waste loads by using water quality models, as well as combining Gini coefficient and Data Envelopment Analysis (DEA) to assess the relationship between the equity levels and the maximum waste load. It is also discussed that the impacts of changes in the land use among up- stream and down-stream on assimilative capacity and equity, which can provide useful information for the policy making of sustainable watershed management.
H43A-0967
Recent Trends in USA streamflow: Implications for the Water Cycle
Streamflow provides one of the best indications of changes in the water cycle over land. Most previous analyses of changes in streamflow over decadal timescales have been limited by uncertainty over the impact of land-use change and water diversion and by poor quantification of measurement errors. We mapped annual runoff over the conterminous USA since 1920 based on stream gauge measurements in primarily small, minimally disturbed drainage basins from the (USGS) Hydro-Climatic Data Network (HCDN), using geostatistical methods to estimate the uncertainty in our estimates of areally integrated runoff due to small-scale variability, missing data, and measurement error. We found that runoff generally increased over the period 1940-1990, paralleling increases in precipitation, with a particularly sharp rise in the early 1970s, but has not risen since the early 1990s. Annual runoff shows no significant correlation with local or global temperature over the entire time period. The observed failure of streamflow as well as precipitation over midlatitude land to increase with recent warming speaks against a general "acceleration of the hydrologic cycle" and implies a high risk of reduced water supplies and increased plant water stress with continued warming in coming decades.
H43A-0968
Effects of Climate Variability on Water Storage in the Colorado River Basin
The Colorado river is one of the most important sources of surface water in the Western United States and it is vital to drinking water supplies in the Southwestern United States. Estimating intra- and inter-annual variability of water storage in the basin is important for sustainable water management. Several methods to estimate basin scale terrestrial water storage (TWS) change were applied to the Colorado River basin. The methods reported here are the Basin-Scale Water Balance (BSWB) method and distributed hydrological modeling. The BSWB- method uses atmospheric moisture convergence and precipitable water from reanalysis data, together with naturalized streamflow. We use two different reanalysis datasets, i.e., the European Center for Medium-range Weather Forecasts dataset, spanning the period from 1958 to 2005, and the North American Regional Reanalysis (NARR), spanning the period from 1979 to 2005. The land surface hydrologic model (VIC: Variable Infiltration Capacity) is forced with gridded meteorological observations spanning the period between 1949 and 2005. The three TWS-change estimates show, apart from a strong annual cycle, a longer, near-decadal cycle. This suggests an impact of long-term climate variability. The hydrological regime in the Colorado basin has been linked to various indices of climate variability. Examples are the El-Nino/Southern Oscillation (ENSO), which is the most important and the best predictable one, and the less predictable Pacific Decadal Oscillation (PDO). In this study, a range of climate variability indices is investigated. When annual cycles are filtered out, especially ENSO, the East-Pacific/North-Pacific pattern and Scandinavia pattern seem to be correlated to the TWS-change signal in the Colorado basin, although this correlation is highest for the BSWB-NARR TWS-estimate. The combined effect of the climate variability modes influencing TWS in the Colorado basin is further examined. Although it is difficult to link a single climate index to TWS changes in the basin, investigating the effects of the combination of indices affecting TWS can potentially improve its predictability, contributing to sustainable water management in the region.
H43A-0969
Paleoflood Hydrology of the Dolores River, Colorado and Utah
Field evidence from three paleostage indicators suggests at least four extreme flood events have occurred on the Dolores River in the past 2,000-years. The landscape position and sediment texture from the paleostage indicators reveal peak discharges that exceed those of the gauged or historical record. Additionally, evidence from one of the paleostage indicator suggests a high-discharge, hyperconcentrated flow event that occurred even more recently and lies ~8m above the present river elevation. Two of the paleostage indicators are slack- water deposits; one is in a sheltered cave and another on the lee side of a large rock outcrop. The other paleoflood deposit is an overbank slack-water deposit. At each slack-water site, we collected organic materials and sediment samples for radiocarbon and optically stimulated luminescence (OSL) dating. Preliminary correlations exist between two paleoflood units based on sediment color, texture and stratigraphic position. This is the first paleoflood study of the Dolores River and it is one of the final remaining, major tributaries of the upper Colorado River Watershed to be studied from a paleoflood perspective. The Dolores River is of particular interest because slack-water deposits located on the Colorado River suggest the Dolores River is the primary source for an extreme discharge event that occurred <2,000 years ago. That flood had an estimated discharge of 8,500 cm3s-1 (more than two-times the magnitude of the largest historical flood of 1884). The aim of this study is to determine correlations between the extreme flood that occurred on the Colorado River with the paleohydrologic record of extreme events on the Dolores River.
H43A-0970
Drought on the Colorado River: Is the most recent decade of low flows unusual?
Stakeholder and users, from water resource managers to governors, have begun to ask if the past decade of runoff patterns and streamflows levels in the upper Colorado River Basin are harbingers of the future climate changes. Over the last 10 years, the streamflow has been 83 percent of the average (1971-2000). Increasingly, users are posing questions about projected future changes in the context of past changes. Some of these questions include: Is this recent decade of flows a departure from long-term averages? And are similar conditions likely to persist into the future? To address these questions, we examine the 1998-2007 decade of Colorado River flows in context of several records: the 1964 to present unregulated inflow into Lake Powell, the 1896 to present natural flow at Lees Ferry estimates, and the 500+ year tree ring reconstructions of streamflow at Lees Ferry extrapolated to present. We test whether the means of various segments of the records are different than the means of the full records. We also test whether dry periods persist longer than would be expected from randomly derived sequences. Results are compared to similar analyses of drought risk in 500+ year tree ring reconstructions of streamflow. Our study underscores the importance determining the changing baselines that decision makers confront in planning for the future based on limited instrumental records and hydroclimatic systems in transition