Macroscale Hydrologic Model Research Articles

Implications of climate-driven variability and trends for the hydrologic assessment of the Reynolds Creek Experimental Watershed, Idaho

Summary The Soil and Water Assessment Tool (SWAT) model was used to assess the implications of long-term climate trends for the hydroclimatology of the Reynolds Creek Experimental Watershed (RCEW) in the Owyhee Mountains, Idaho of the Intermountain West over a 40-year period (1967–2006). Calibration and validation of the macroscale hydrology model in this highly monitored watershed is key to address the watershed processes that are vulnerable to both natural climate variability and climate change. The model was calibrated using the streamflow data collected between 1997 and 2006 from the three nested weirs, the Reynolds Mountain East (RME), Tollgate and Outlet. For assessing the performance of the calibrated model, this study used 30 years of streamflow data for the period between 1966 and 1996. This investigation suggested that the model predicted streamflow was best at RME, and inadequate at Outlet. Simulated soil moisture was also verified using the data available from five soil moisture measurement sites. The model was able to capture the seasonal patterns of changes in soil water storage considering the differences in the spatial extent of the observed and predicted soil water storage (point measurements against the spatially averaged values for the HRU) and uncertainty associated with the soil moisture measurements due to instrument effects. Water budget partitioning during a wet (1984) water year and a dry (1987) water year were also analyzed to characterize the differences in hydrologic cycles during the extreme hydrologic conditions. Our analysis showed that in the dry water year, vegetation at the higher elevation were under water stress by the end of the water year. Contrastingly, in the wet water year only the vegetation at low and mid-elevations were under water stress whereas vegetation at the higher elevations derived substantial soil moisture for ET processes even towards the end of the growing season. To understand the effect of climate change on the hydrologic cycle, the observed and simulated streamflow were analyzed for trends in Center of Timing (CT). Earlier CT timings for the simulated and observed streamflow at RME weir was obvious thus manifesting global warming signals at the watershed scale level in the Intermountain west region. Observed streamflow at the Tollgate and Outlet weirs, where streamflow is partially affected by the agricultural diversions, showed later CT timings and these results appeared to suggest that climate impact assessment studies need to carefully distinguish the system behavior that is altered by both natural and human-induced changes.

Changes in Streamflow Dynamics in the Rhine Basin under Three High-Resolution Regional Climate Scenarios

Abstract Because of global warming, the hydrologic behavior of the Rhine basin is expected to shift from a combined snowmelt- and rainfall-driven regime to a more rainfall-dominated regime. Previous impact assessments have indicated that this leads, on average, to increasing streamflow by ∼30% in winter and spring and decreasing streamflow by a similar value in summer. In this study, high-resolution (0.088°) regional climate scenarios conducted with the regional climate model REMO (REgional MOdel) for the Rhine basin are used to force a macroscale hydrological model. These climate scenarios are based on model output from the ECHAM5–Max Planck Institute Ocean Model (MPI-OM) global climate model, which is in turn forced by three Special Report on Emissions Scenarios (SRES) emission scenarios: A2, A1B, and B1. The Variable Infiltration Capacity model (VIC; version 4.0.5) is used to examine changes in streamflow at various locations throughout the Rhine basin. Average streamflow, peak flows, low flows, and several water balance terms are evaluated for both the first and second half of the twenty-first century. The results reveal a distinct contrast between those periods. The first half is dominated by increased precipitation, causing increased streamflow throughout the year. During the second half of the century, a streamflow increase in winter/spring and a decrease in summer is found, similar to previous studies. This is caused by 1) temperature and evapotranspiration, which are considerably higher during the second half of the century; 2) decreased precipitation in summer; and 3) an earlier start of the snowmelt season. Magnitudes of peak flows increase during both periods, and the magnitudes of streamflow droughts increase only during the second half of the century.

Hydrologic impacts of climate change on the Nile River Basin: implications of the 2007 IPCC scenarios

We assess the potential impacts of climate change on the hydrology and water resources of the Nile River basin using a macroscale hydrology model. Model inputs are bias corrected and spatially downscaled 21st Century simulations from 11 General Circulation Models (GCMs) and two global emissions scenarios (A2 and B1) archived from the 2007 IPCC Fourth Assessment Report (AR4). While all GCMs agree with respect to the direction of 21st Century temperature changes, there is considerable variability in the magnitude, direction, and seasonality of projected precipitation changes. Our simulations show that, averaged over all 11 GCMs, the Nile River is expected to experience increase in streamflow early in the study period (2010-2039), due to generally increased precipitation. Streamflow is expected to decline during mid- (2040-2069) and late (2070-2099) century as a result of both precipitation declines and increased evaporative demand. The predicted multimodel average streamflow at High Aswan Dam (HAD) as a percentage of historical (1950- 1999) annual average are 111 (114), 92 (93) and 84 (87) for A2 (B1) global emissions scenarios. Implications of these streamflow changes on the water resources of the Nile River basin were analyzed by quantifying the annual hydropower production and irrigation water release at HAD. The long-term HAD release for irrigation increases early in the century to 106 (109)% of historical, and then decreases to 87 (89) and 86 (84)% of historical in Periods II and III, respectively, for the A2 (B1) global emissions scenarios. Egypt's hydropower production from HAD will be above the mean annual average historical value of about 10,000 GWH for the early part of 21st century, and thereafter will generally follow the streamflow trend, however

Modelling blowing snow redistribution to prairie wetlands

AbstractBlowing snow transports and sublimates a substantial portion of the seasonal snowfall in the prairies of western Canada. Snow redistribution is an important feature of prairie hydrology as deep snowdrifts provide a source of meltwater to replenish ponds and generate streamflow in this dry region. The spatial distribution of snow water equivalent in the spring is therefore of great interest. A test of the distributed and aggregated modelling strategies for blowing snow transport and sublimation was conducted at the St. Denis National Wildlife Area in the rolling, internally drained prairie pothole region east of Saskatoon, Saskatchewan, Canada. A LiDAR‐based DEM and aerial photograph‐based vegetation cover map were available for this region. A coupled complex windflow and blowing snow model was run with 262,144 6 m × 6 m grid cells to produce spatially distributed estimates of seasonal blowing snow transport and sublimation. The calculation was then aggregated to seven landscape units that represented the major influences of surface roughness, topography and fetch on blowing snow transport and sublimation. Both the distributed and aggregated simulations predicted similar end‐of‐winter snow water equivalent with substantial redistribution of blowing snow from exposed sparsely vegetated sites across topographic drainage divides to the densely vegetated pothole wetlands. Both simulations also agreed well with snow survey observations. While the distributed calculations provide a fascinating and detailed visual image of the interaction of complex landscapes and blowing snow redistribution and sublimation, it is clear that blowing snow transport and sublimation calculations can be successfully aggregated to the spatial scale of the major landscape units in this environment. This means that meso and macroscale hydrological models can represent blowing snow redistribution successfully in the prairies. Copyright © 2009 John Wiley & Sons, Ltd.

The significance of local water resources captured in small reservoirs for crop production – A global-scale analysis

Summary Rainwater harvesting, broadly defined as the collection and storage of surface runoff, has a long history in supplying water for agricultural purposes. Despite its significance, rainwater harvesting in small reservoirs has previously been overlooked in large-scale assessments of agricultural water supply and demand. We used a macroscale hydrological model, observed climate data and other physical datasets to explore the potential role of small, localized rainwater harvesting systems in supplying water for irrigated areas. We first estimated the potential contribution of local water harvesting to supply currently irrigated areas. We then explored the potential of supplemental irrigation applied to all cropland areas to increase crop evapotranspiration (or green water flow), using locally stored surface runoff in small reservoirs for different scenarios of installed reservoir capacity. The estimated increase in green water flow varied between 623 and 1122 km 3 a −1 . We assessed the implications of this increase in green water flows for cereal production by assuming a constant crop water productivity in areas where current levels of crop yield are below global averages. Globally, the supplemental irrigation of existing cropland areas could increase cereal production by ∼35% for a medium variant of reservoir capacity, with large potential increases in Africa and Asia. As small reservoirs can significantly impact the hydrological regime of river basins, we also assessed the impacts of small reservoirs on downstream river flow and quantified evaporation losses from small reservoirs.

Spatial averaging infiltration model for layered soil

To quantify the influences of soil heterogeneity on infiltration, a spatial averaging infiltration model for layered soil (SAI model) is developed by coupling the spatial averaging approach proposed by Chen et al. and the Generalized Green-Ampt model proposed by Jia et al. In the SAI model, the spatial heterogeneity along the horizontal direction is described by a probability distribution function, while that along the vertical direction is represented by the layered soils. The SAI model is tested on a typical soil using Monte Carlo simulations as the base model. The results show that the SAI model can directly incorporate the influence of spatial heterogeneity on infiltration on the macro scale. It is also found that the homogeneous assumption of soil hydraulic conductivity along the horizontal direction will overestimate the infiltration rate, while that along the vertical direction will underestimate the infiltration rate significantly during rainstorm periods. The SAI model is adopted in the spatial averaging hydrological model developed by the authors, and the results prove that it can be applied in the macro-scale hydrological and land surface process modeling in a promising way.

A Generalized Subsurface Flow Parameterization Considering Subgrid Spatial Variability of Recharge and Topography

Abstract Subsurface flow is an important hydrologic process and a key component of the water budget. Through its direct impacts on soil moisture, it can affect water and energy fluxes at the land surface and influence the regional climate and water cycle. In this study, a new subsurface flow formulation is developed that incorporates the spatial variability of both topography and recharge. It is shown through theoretical derivation and case studies that the power-law and exponential subsurface flow parameterizations and the parameterization proposed by Woods et al. are all special cases of the new formulation. The subsurface flows calculated using the new formulation compare well with values derived from observations at Tulpehocken Creek, Pennsylvania, and Walnut Creek, Iowa. Sensitivity studies show that when the spatial variability of topography or recharge, or both is increased, the subsurface flows increase at the two aforementioned sites and at the Maimai hillslope, New Zealand. This is likely due to enhancement of interactions between the groundwater table and the land surface that reduce the flow path. An important conclusion of this study is that the spatial variability of recharge alone, and/or in combination with the spatial variability of topography can substantially alter the behaviors of subsurface flows. This suggests that in macroscale hydrologic models or land surface models, subgrid variations of recharge and topography can make significant contributions to the grid mean subsurface flow and must be accounted for in regions with large surface heterogeneity. This is particularly true for regions with humid climate and a relatively shallow groundwater table where the combined impacts of spatial variability of recharge and topography are shown to be more important. For regions with an arid climate and a relatively deep groundwater table, simpler formulations, for example, the power law, for subsurface flow can work well, and the impacts of subgrid variations of recharge and topography may be ignored.

A Catchment‐Based Hydrologic and Routing Modeling System with explicit river channels

In this paper, we present a macroscale hydrologic modeling system with an explicit representation of storage and movement of water in river channels and floodplains. The overall modeling system, called the Catchment‐Based Hydrologic and Routing Modeling System (CHARMS), is composed of a land surface model and a river routing model that operate on a network of hydrologic catchments (or watersheds). The land surface model in CHARMS is based on the National Center for Atmospheric Research Community Land Model. The river routing model in CHARMS generates river discharge by transporting runoff generated by the catchment‐based CLM through the river network. The routing model uses information on channel cross‐section geometry, derived from the 90 m Shuttle Radar Topography Mission digital elevation model, to simulate river discharge and the associated flow depth and inundation width. CHARMS was implemented over the Wabash River basin in the central United States (drainage area 72282 km2), and simulated streamflow was validated using daily observations. Simulated flow depth and inundation extent generally followed seasonal variations in observed flooding and droughts. Limitations of some of the assumptions and scaling factors used in this study and the issues that need to be addressed for a continental‐ or global‐scale implementation of CHARMS are discussed. This paper serves as the foundation for a catchment‐based, global land surface modeling framework that could incorporate spatiotemporal variations in surface water bodies, as well as satellite measurements of these variations.

Evaluation of Precipitation Products for Global Hydrological Prediction

Abstract Accurate precipitation data are critical for hydrologic prediction, yet outside the developed world in situ networks are so sparse as to make alternative methods of precipitation estimation essential. Several such alternative precipitation products that would be adequate to drive hydrologic prediction models at regional and global scales are evaluated. As a benchmark, a gridded station-based dataset is used, which is compared with the global 40-yr ECMWF Re-Analysis (ERA-40), and a satellite-based dataset [i.e., the Global Precipitation Climatology Project One-Degree Daily (GPCP 1DD)]. Each dataset, with a common set of other meteorological forcings aside from precipitation, was used to force the Variable Infiltration Capacity (VIC) macroscale hydrology model globally for the 1997–99 period for which the three datasets overlapped. The three precipitation datasets and simulated hydrological variables (i.e., soil moisture, runoff, evapotranspiration, and snow water equivalent) are compared in terms of the implied water balances of the continents, and for prediction of streamflow for nine large river basins. The evaluations are in general agreement with previous but more local evaluations of precipitation products and water balances: the precipitation datasets agree reasonably on the seasonality but less on monthly anomalies. Furthermore, the largest differences in precipitation are in mountainous regions and regions where in situ networks are sparse (such as Africa). Derived runoff is highly sensitive to differences in precipitation forcings. At a global level, all three simulations result in water budgets that are within the range of other water balance climatologies. Although uncertainties in the three datasets preclude an evaluation of which one has the lowest errors, overall ERA-40 is preferred because of its agreement with the station-based dataset in locations where the station density is high, its periodic availability, and its temporal resolution.

A multimodel ensemble approach to assessment of climate change impacts on the hydrology and water resources of the Colorado River Basin

Abstract. Implications of 21st century climate change on the hydrology and water resources of the Colorado River Basin were assessed using a multimodel ensemble approach in which downscaled and bias corrected output from 11 General Circulation Models (GCMs) was used to drive macroscale hydrology and water resources models. Downscaled climate scenarios (ensembles) were used as forcings to the Variable Infiltration Capacity (VIC) macroscale hydrology model, which in turn forced the Colorado River Reservoir Model (CRMM). Ensembles of downscaled precipitation and temperature, and derived streamflows and reservoir system performance were assessed through comparison with current climate simulations for the 1950–1999 historical period. For each of the 11 GCMs, two emissions scenarios (IPCC SRES A2 and B1, corresponding to relatively unconstrained growth in emissions, and elimination of global emissions increases by 2100) were represented. Results for the A2 and B1 climate scenarios were divided into three periods: 2010–2039, 2040–2069, and 2070–2099. The mean temperature change averaged over the 11 ensembles for the Colorado basin for the A2 emission scenario ranged from 1.2 to 4.4°C for periods 1–3, and for the B1 scenario from 1.3 to 2.7°C. Precipitation changes were modest, with ensemble mean changes ranging from −1 to −2% for the A2 scenario, and from +1 to −1% for the B1 scenario. An analysis of seasonal precipitation patterns showed that most GCMs had modest reductions in summer precipitation and increases in winter precipitation. Derived April 1 snow water equivalent declined for all ensemble members and time periods, with maximum (ensemble mean) reductions of 38% for the A2 scenario in period 3. Runoff changes were mostly the result of a dominance of increased evapotranspiration over the seasonal precipitation shifts, with ensemble mean runoff changes of −1, −6, and −11% for the A2 ensembles, and 0, −7, and −8% for the B1 ensembles. These hydrological changes were reflected in reservoir system performance. Average total basin reservoir storage and average hydropower production generally declined, however there was a large range across the ensembles. Releases from Glen Canyon Dam to the Lower Basin were reduced for all periods and both emissions scenarios in the ensemble mean. The fraction of years in which shortages occurred increased by approximately 20% by period 3 for both emissions scenarios.

Monte Carlo sensitivity analysis of land surface parameters using the Variable Infiltration Capacity model

Current land surface models use increasingly complex descriptions of the processes that they represent. Increase in complexity is accompanied by an increase in the number of model parameters, many of which cannot be measured directly at large spatial scales. A Monte Carlo framework was used to evaluate the sensitivity and identifiability of ten parameters controlling surface and subsurface runoff generation in the Variable Infiltration Capacity model (VIC). Using the Monte Carlo Analysis Toolbox (MCAT), parameter sensitivities were studied for four U.S. watersheds along a hydroclimatic gradient, based on a 20‐year data set developed for the Model Parameter Estimation Experiment (MOPEX). Results showed that simulated streamflows are sensitive to three parameters when evaluated with different objective functions. Sensitivity of the infiltration parameter (b) and the drainage parameter (exp) were strongly related to the hydroclimatic gradient. The placement of vegetation roots played an important role in the sensitivity of model simulations to the thickness of the second soil layer (thick2). Overparameterization was found in the base flow formulation indicating that a simplified version could be implemented. Parameter sensitivity was more strongly dictated by climatic gradients than by changes in soil properties. Results showed how a complex model can be reduced to a more parsimonious form, leading to a more identifiable model with an increased chance of successful regionalization to ungauged basins. Although parameter sensitivities are strictly valid for VIC, this model is representative of a wider class of macroscale hydrological models. Consequently, the results and methodology will have applicability to other hydrological models.

Effects of 20th century warming and climate variability on flood risk in the western U.S.

Using precipitation and temperature data for the 20th century in combination with a macroscale hydrologic model, we evaluate changes in flood risk in the western U.S. associated both with century‐scale warming and interannual climate variations. In addition, we examine the implications of apparent increases in precipitation variability over the region since the mid‐1970s. We use detrended temperature data representing early and late 20th century climate to force the variable infiltration capacity hydrologic model and show that spatially homogeneous temperature changes over the western U.S. in the 20th century on the order of +1°C per century have resulted in substantial changes in flood risks over much of the region. Although changes specific to particular geographic areas are apparent in some cases, the overall changes due to observed warming trends are well categorized by midwinter temperature regimes in each watershed. Cold river basins where snow processes dominate the annual hydrologic cycle (<−6°C average in midwinter) typically show reductions in flood risk due to overall reductions in spring snowpack. Relatively warm rain‐dominant basins (>5°C average in midwinter) show little systematic change. Intermediate or transient basins show a wide range of effects depending on competing factors such as the relative role of antecedent snow and contributing basin area during storms that cause flooding. Warmer transient basins along the coast in Washington, Oregon, and California, in particular, tend to show increased flood risk. While the absolute value of simulated changes in flood risk is affected by basin scale, the nature of the relationship of flood risk to basin temperatures in midwinter is largely scale‐independent. Climate variations associated with Pacific Decadal Oscillation (PDO) and El Niño Southern Oscillation (ENSO) also have strong effects on flood risks. In contrast to the effects associated with 20th century warming, the climate variability signal is characterized by regional scale patterns related to the geographic distribution of cool season precipitation also identified in many previous studies. In general, the largest changes in simulated flood risks are associated with years when PDO and ENSO are “in phase,” particularly in the southwest. Changes in the variability of cool season precipitation after about 1973, the causes of which are uncertain, are shown to result in increased flood risk over much of the western U.S. in the simulations.

Hydrologic effects of land and water management in North America and Asia: 1700–1992

Abstract. The hydrologic effects of land use changes, dams, and irrigation in North America and Asia over the past 300 years are studied using a macroscale hydrologic model. The simulation results indicate that the expansion of croplands over the last three centuries has resulted in 2.5 and 6 percent increases in annual runoff volumes for North America and Asia, respectively, and that these increases in runoff to some extent have been compensated by increased evapotranspiration caused by irrigation practices. Averaged over the year and the continental scale, the accumulated anthropogenic impacts on surface water fluxes are hence relatively minor. However, for some regions within the continents human activities have altered hydrologic regimes profoundly. Reservoir operations and irrigation practices in the western part of USA and Mexico have resulted in a 25 percent decrease in runoff in June, and a 9 percent decrease in annual runoff volumes reaching the Pacific Ocean. In the area in South East Asia draining to the Pacific Ocean, land use changes have caused an increase in runoff volumes throughout the year, and the average annual increase in runoff is 12 percent.

Thirty‐five year (1971–2005) simulation of daily soil moisture using the variable infiltration capacity model over China

We use the Variable Infiltration Capacity (VIC) land surface macroscale hydrology model driven by observed maximum and minimum air temperatures and precipitation to map daily soil moisture values over China for the period 1 January 1971 to 31 July 2005. The model is applied over a grid of 10 458 points with a resolution of 30 km × 30 km. The model is first calibrated using observed hydrographs from 35 catchments with drainage areas varying from 190 to 351 530 km2. The model is then validated over these 35 catchments at different periods, and over an additional eight catchments with drainage areas ranging from 1230 to 10 010 km2. An estimation procedure to determine model parameters is developed and applied to catchments where hydrographs are not available for the standard calibration process. In situ soil moisture measurements from 28 sites around the country are also used for model validation. VIC performs well over both calibration and validation catchments especially in humid and semi‐humid regions. The 35‐year soil moisture climatology for the top 1 m from VIC is consistent with known soil moisture conditions in China.

Evaluation of surface water fluxes of the pan‐Arctic land region with a land surface model and ERA‐40 reanalysis

The seasonal, spatial, and latitudinal variability of precipitation (P), evapotranspiration (E), and runoff (R) are examined for large Arctic river basins and for the entire pan‐Arctic domain using a 21‐year off‐line simulation of the Variable Infiltration Capacity (VIC) macroscale hydrology model and the ERA‐40 reanalysis. Observed P used in the VIC model (corrected for gauge catch deficiency) is compared with that from the ERA‐40 reanalysis. Gridded values of evapotranspiration minus precipitation (E‐P) are calculated from the ERA‐40 atmospheric water budget, and estimates of implied E are obtained as the residual of observed P and ERA‐40 E‐P. The ERA‐40 P is surprisingly close to observations on an annual basis over the large river basins (especially accounting for known errors in the observations). Furthermore, ERA‐40 P is quite consistent with observations in terms of interannual, spatial, and latitudinal variations. ERA‐40 E is generally higher than both VIC E and implied E in spring and autumn. However, VIC estimates more E in June and July than either ERA‐40 or the atmospheric budget for the Yenisei, Ob, and Mackenzie River basins. The ERA‐40 bias toward early snowmelt and a double runoff peak (not present in VIC or observations) indicates the need for improvements in the ECMWF land surface scheme. The long‐term means of ERA‐40 vapor convergence P‐E for the Lena, Yenisei, Ob, and Mackenzie are not in balance with observed runoff, mainly due to the uncertainties in computed P‐E and observed streamflow.

Use of Satellite Data for Streamflow and Reservoir Storage Forecasts in the Snake River Basin

We describe an approach to seasonal streamflow forecasting for the Snake River Basin in the Pacific Northwest that uses the variable infiltration capacity (VIC) macroscale hydrology model in conjunction with adjustments of the model’s initial snow state using moderate resolution imaging spectroradiometer (MODIS) imagery for Winters 2000–2004. We evaluated seasonal streamflow forecasts made on March 1, April 1, and May 1 through the end of July, as well as short lead forecasts for two-week durations beginning on April 15 and May 15 retrospectively for 2000–2004 (2004 forecasts are archived forecasts made in real time). In general, reductions in mean absolute error were more prevalent and larger for the two-week forecasts than for the longer seasonal forecasts, and the forecast skill improvements resulting from updating were greatest for forecasts made earliest in the season. Inclusion of MODIS data resulted in forecast error reduction (or no change in forecasts) in 59% of the seasonal forecasts (54% of the...

Input data resolution analysis for distributed hydrological modeling

A distributed hydrological model is often needed to analyze spatially variable hydrologic behavior. Such a model can be difficult to set up, especially for an ungauged basin, as it demands a massive amount of data. Moreover, there is an additional challenge of selecting a proper grid resolution as the grid size selection generally leads to predictive uncertainty and also directly determines the amount of work required. In this study, a distributed macro-scale hydrological model, named as the MaScOD model, is applied with a 10-min spatial resolution to the Huaihe River basin, China, to simulate discharge at Bengbu (132,350 km 2) and at sub-basins at Wangjiaba (29,844 km 2) and at Suiping (2093 km 2). A range of input data resolutions are used, from 10 min to 2.5°, based on an experimental hydro-meteorological input data set abstracted from the GAME re-analysis data and the Hubex-IOP EEWB data. Performance of the model is evaluated by comparing observed discharge against simulated discharge for a range of IC-ratio values (the ratio between the input forcing resolution and the Catchment area). Similar results are obtained for all three catchments, despite their different sizes. It is found that improvement in distributed model performance is more pronounced below the IC-ratio 1:10, whereas the rate of improvement is negligible above the IC-ratio 1:20. The IC-ratio range 1:10–1:20 is found to be the optimum performance range considering the data and resource demands of distributed models. This may provide a preliminary criterion for selecting the scale for distributed hydrological modeling in ungauged basins.

Twentieth-Century Drought in the Conterminous United States

Abstract Droughts can be characterized by their severity, frequency and duration, and areal extent. Depth–area–duration analysis, widely used to characterize precipitation extremes, provides a basis for the evaluation of drought severity when storm depth is replaced by an appropriate measure of drought severity. Gridded precipitation and temperature data were used to force a physically based macroscale hydrologic model at 1/2° spatial resolution over the continental United States, and construct a drought history from 1920 to 2003 based on the model-simulated soil moisture and runoff. A clustering algorithm was used to identify individual drought events and their spatial extent from monthly summaries of the simulated data. A series of severity–area–duration (SAD) curves were constructed to relate the area of each drought to its severity. An envelope of the most severe drought events in terms of their SAD characteristics was then constructed. The results show that (a) the droughts of the 1930s and 1950s were the most severe of the twentieth century for large areas; (b) the early 2000s drought in the western United States is among the most severe in the period of record, especially for small areas and short durations; (c) the most severe agricultural droughts were also among the most severe hydrologic droughts, however, the early 2000s western U.S. drought occupies a larger portion of the hydrologic drought envelope curve than does its agricultural companion; and (d) runoff tends to recover in response to precipitation more quickly than soil moisture, so the severity of hydrologic drought during the 1930s and 1950s was dampened by short wet spells, while the severity of the early 2000s drought remained high because of the relative absence of these short-term phenomena.

Effects of irrigation on the water and energy balances of the Colorado and Mekong river basins

An irrigation scheme, based on simulated soil moisture deficit, has been included in the variable infiltration capacity macroscale hydrologic model. Water withdrawals are taken from the nearest river, or, in periods of water scarcity, from reservoirs. Alternatively, water can be assumed freely available. The irrigation scheme successfully simulates crop consumptive water use in large river basins. In general, irrigation leads to decreased streamflow and increased evapotranspiration. The locally significant increases in evapotranspiration (or latent heat) results in lower surface temperatures, and hence decreased sensible heat flux. Simulations performed for a 20-year period for the Colorado and Mekong river basins indicate irrigation water requirements of 10 and 13.4 km 3 year −1, respectively, corresponding to streamflow decreases of 37 and 2.3%. The increase in latent heat flux is accompanied by a decrease in annual averaged surface temperatures of 0.04 °C for both river basins. The maximum simulated increase in latent heat flux averaged over the three peak irrigation months for one grid cell is 63 W m −2, where surface temperature decreases 2.1 °C. Simulated actual water use is somewhat less than simulated irrigation water requirements; 8.3 and 12.4 km 3 year −1 for the Colorado and Mekong river basin, respectively.

Assimilating remotely sensed snow observations into a macroscale hydrology model

Accurate forecasting of snow properties is important for effective water resources management, especially in mountainous areas like the western United States. Current model-based forecasting approaches are limited by model biases and input data uncertainties. Remote sensing offers an opportunity for observation of snow properties, like areal extent and water equivalent, over larger areas. Data assimilation provides a framework for optimally merging information from remotely sensed observations and hydrologic model predictions. An ensemble Kalman filter (EnKF) was used to assimilate remotely sensed snow observations into the variable infiltration capacity (VIC) macroscale hydrologic model over the Snake River basin. The snow cover extent (SCE) product from the moderate resolution imaging spectroradiometer (MODIS) flown on the NASA Terra satellite was used to update VIC snow water equivalent (SWE), for a period of four consecutive winters (1999–2003). A simple snow depletion curve model was used for the necessary SWE–SCE inversion. The results showed that the EnKF is an effective and operationally feasible solution; the filter successfully updated model SCE predictions to better agree with the MODIS observations and ground surface measurements. Comparisons of the VIC SWE estimates following updating with surface SWE observations (from the NRCS SNOTEL network) indicated that the filter performance was a modest improvement over the open-loop (un-updated) simulations. This improvement was more evident for lower to middle elevations, and during snowmelt, while during accumulation the filter and open-loop estimates were very close on average. Subsequently, a preliminary assessment of the potential for assimilating the SWE product from the advanced microwave scanning radiometer (AMSR-E, flown on board the NASA Aqua satellite) was conducted. The results were not encouraging, and appeared to reflect large errors in the AMSR-E SWE product, which were also apparent in comparisons with SNOTEL data.