Decoupling Streamflow Responses to Climate Variability and Land Use/Cover Changes in a Watershed in Northern China

Restored annual streamflow (Q_r) and measured daily streamflow of the Chaohe watershed located in northern China and associated long‐term climate and land use/cover data were used to explore the effects of land use/cover change and climate variability on the streamflow during 1961‐2009. There were no significant changes in annual precipitation (P) and potential evapotranspiration, whereas Q_r decreased significantly by 0.81 mm/yr (p < 0.001) over the study period with a change point in 1999. We used 1961‐1998 as the baseline period (BP) and 1999‐2009 the change period (CP). The mean Q_r during the CP decreased by 39.4 mm compared with that in the BP. From 1979 to 2009, the grassland area declined by 69.6%, and the forest and shrublands increased by 105.4 and 73.1%, respectively. The land use/cover change and climate variability contributed for 58.4 and 41.6% reduction in mean annual Q_r, respectively. Compared with the BP, median and high flows in the CP decreased by 38.8 and up to 75.5%, respectively. The study concludes that large‐scale ecological restoration and watershed management in northern China has greatly decreased water yield and reduced high flows due to the improved land cover by afforestation leading to higher water loss through evapotranspiration. At a large watershed scale, land use/cover change could play as much of an important role as climate variability on water resources.     

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.     

Estimation of Evapotranspiration Across the Conterminous United States Using a Regression With Climate and Land‐Cover Data1

Sanford, Ward E. and David L. Selnick, 2012. Estimation of Evapotranspiration Across the Conterminous United States Using a Regression with Climate and Land‐Cover Data. Journal of the American Water Resources Association (JAWRA) 1‐14. DOI: 10.1111/jawr.12010 Abstract: Evapotranspiration (ET) is an important quantity for water resource managers to know because it often represents the largest sink for precipitation (P) arriving at the land surface. In order to estimate actual ET across the conterminous United States (U.S.) in this study, a water‐balance method was combined with a climate and land‐cover regression equation. Precipitation and streamflow records were compiled for 838 watersheds for 1971‐2000 across the U.S. to obtain long‐term estimates of actual ET. A regression equation was developed that related the ratio ET/P to climate and land‐cover variables within those watersheds. Precipitation and temperatures were used from the PRISM climate dataset, and land‐cover data were used from the USGS National Land Cover Dataset. Results indicate that ET can be predicted relatively well at a watershed or county scale with readily available climate variables alone, and that land‐cover data can also improve those predictions. Using the climate and land‐cover data at an 800‐m scale and then averaging to the county scale, maps were produced showing estimates of ET and ET/P for the entire conterminous U.S. Using the regression equation, such maps could also be made for more detailed state coverages, or for other areas of the world where climate and land‐cover data are plentiful.     

Evapotranspiration in the Meso‐Scale Forested Watersheds in Minjiang Valley,West China1

Abstract: Information on evapotranspiration (ET) can help us understand water balance, particularly in forested watersheds. Previous studies in China show that ET was relatively low (30‐40% of total precipitation) in the Minjiang Valley located in the upper reach of the Yangtze River Basin. However, this conclusion was derived from research on small‐scale watersheds (<100 km²). The objective of this paper was to present ET information on meso‐scale watersheds in the Minjiang Valley. Four meso‐scale watersheds (1,700‐5,600 km²) located in the Minjiang Valley were used to estimate ET using the water balance approach. We first generated forest vegetation variables (coniferous forest percentage, forest cover percentage, and derived forest vegetation index) using remote sensing data. Landsat 5 TM satellite images, acquired on June 26, 1994, were selected for the vegetation classification. Actual annual ET was calculated based on 11‐year estimated precipitation and measured streamflow data (1992‐2002). We also calculated potential ET (PET) using an improved Thornthwaite model for all four watersheds for the period of 1992‐1998. PET can provide additional information about potential capacity of water flux to atmosphere in the region. Seasonal (dry and rainy) PET and ET for all studied watersheds were also estimated for comparison purposes as the water balance approach, at shorter than annual scales, would likely provide inaccurate estimates of ET. The dominant vegetations in the Minjiang Valley were grasslands, conifer forests, and shrub‐lands. Our results confirmed that both ET and PET for three studied meso‐scale watersheds in the Minjiang Valley is relatively low (39.5‐43.8 and 28.2‐47.7% for ET and PET, respectively), with an exception of ET in the Yuzixi watershed being 71.1%. This result is generally consistent with previous research at small watershed scales. Furthermore, the low ET across various scales in the Minjiang Valley may be related to the unique deeply cut valley environment.     

BASE FLOW RECESSION RATES,LOW FLOWS,AND HYDROLOGIC FEATURES OF SMALL WATERSHEDS IN PENNSYLVANIA,USA1

This paper examines the relationships between measurable watershed hydrologic features, base flow recession rates, and the Q_7,10 low flow statistic (the annual minimum seven‐day average streamflow occurring once every 10 years on average). Base flow recession constants were determined by analyzing hydrograph recession data from 24 small (>130 km²), unregulated watersheds across five major physiographic provinces of Pennsylvania, providing a highly variable dataset. Geomorphic, hydrogeologic, and land use parameters were determined for each watershed. The base flow recession constant was found to be most strongly correlated to drainage density, geologic index, and ruggedness number (watershed slope); however, these three parameters are intercorrelated. Multiple regression models were developed for predicting the recession rate, and it was found that only two parameters, drainage density and hydrologic soil group, were required to obtain good estimates of the recession constant. Equations were also developed to relate the recession rates to Q_7,10 per unit area, and to the Q_7,10/Q₅₀ ratio. Using these equations, estimates of base flow recession rates, Q_7,10, and streamflow reduction under drought conditions can be made for small, ungaged basins across a wide range of physiography.     

Estimating Forest Ecosystem Evapotranspiration at Multiple Temporal Scales With a Dimension Analysis Approach1

Abstract:  It is critical that evapotranspiration (ET) be quantified accurately so that scientists can evaluate the effects of land management and global change on water availability, streamflow, nutrient and sediment loading, and ecosystem productivity in watersheds. The objective of this study was to derive a new semi‐empirical ET modeled using a dimension analysis method that could be used to estimate forest ET effectively at multiple temporal scales. The model developed describes ET as a function of water availability for evaporation and transpiration, potential ET demand, air humidity, and land surface characteristics. The model was tested with long‐term hydrometeorological data from five research sites with distinct forest hydrology in the United States and China. Averaged simulation error for daily ET was within 0.5 mm/day. The annual ET at each of the five study sites were within 7% of measured values. Results suggest that the model can accurately capture the temporal dynamics of ET in forest ecosystems at daily, monthly, and annual scales. The model is climate‐driven and is sensitive to topography and vegetation characteristics and thus has potential to be used to examine the compounding hydrologic responses to land cover and climate changes at multiple temporal scales.     

Sensitivity of Stream flow and Water Table Depth to Potential Climatic Variability in a Coastal Forested Watershed1

Dai, Zhaohua, Carl C. Trettin, Changsheng Li, Devendra M. Amatya, Ge Sun, and Harbin Li, 2010. Sensitivity of Streamflow and Water Table Depth to Potential Climatic Variability in a Coastal Forested Watershed. Journal of the American Water Resources Association (JAWRA) 1–13. DOI: 10.1111/j.1752-1688.2010.00474.x Abstract: A physically based distributed hydrological model, MIKE SHE, was used to evaluate the effects of altered temperature and precipitation regimes on the streamflow and water table in a forested watershed on the southeastern Atlantic coastal plain. The model calibration and validation against both streamflow and water table depth showed that the MIKE SHE was applicable for predicting the streamflow and water table dynamics for this watershed with an acceptable model efficiency (E > 0.5 for daily streamflow and >0.75 for monthly streamflow). The simulation results from changing temperature and precipitation scenarios indicate that climate change influences both streamflow and water table in the forested watershed. Compared to current climate conditions, the annual average streamflow increased or decreased by 2.4% with one percentage increase or decrease in precipitation; a quadratic polynomial relationship between changes in water table depth (cm) and precipitation (%) was found. The annual average water table depth and annual average streamflow linearly decreased with an increase in temperature within the range of temperature change scenarios (0-6°C). The simulation results from the potential climate change scenarios indicate that future climate change will substantially impact the hydrological regime of upland and wetland forests on the coastal plain with corresponding implications to altered ecosystem functions that are dependent on water.     

ANNUAL EVAPOTRANSPIRATION OF NATWE VEGETATION IN A MEDITERRANEAN-TYPE CLIMATE1

ABSTRACT: Annual evapotranspiration from a watershed (ETws) is a function of annual precipitation (P) and fraction of the watershed covered by shrubs and trees (C). Other characteristics are not significant in explaining variance of ETws. A rational equation, ETws = (1-C) ETg + CETst, wherein ETg is the ET of herbaceous cover and ETst is the ET of shrubs and trees, is proposed. The equation has been calibrated for ET and P in inches for the watershed of Lake Cachuma on the Santa Ynez River. This equation, ETmax = 2.14(1-C)P^0.647+ 4.53 C^1.76 P^0.68, is recommended for estimating maximum annual ET demand for conceptual models. Where C is not known, the upper limit of ET = f (P) may be approximated by use of 0.65 for C. The equation has been derived for large unmanaged watersheds. Applicability for evaluation of contemporary multiple purpose vegetation management should be determined by studies of the hydrology of small openings in shrub and tree cover.     

MODIS Biophysical States and NEXRAD Precipitation in a Statistical Evaluation of Antecedent Moisture Condition and Streamflow1

Abstract: The potential of remotely sensed time series of biophysical states of landscape to characterize soil moisture condition antecedent to radar estimates of precipitation is assessed in a statistical prediction model of streamflow in a 1,420 km² watershed in south‐central Texas, Moderate Resolution Imaging Spectroradiometer (MODIS) time series biophysical products offer significant opportunities to characterize and quantify hydrologic state variables such as land surface temperature (LST) and vegetation state and status. Together with Next Generation Weather Radar (NEXRAD) precipitation estimates for the period 2002 through 2005, 16 raw and deseasoned time series of LST (day and night), vegetation indices, infrared reflectances, and water stress indices were linearly regressed against observed watershed streamflow on an eight‐day aggregated time period. Time offsets of 0 (synchronous with streamflow event), 8, and 16 days (leading streamflow event) were assessed for each of the 16 parameters to evaluate antecedent effects. The model results indicated a reasonable correlation (r² = 0.67) when precipitation, daytime LST advanced 16 days, and a deseasoned moisture stress index were regressed against log‐transformed streamflow. The estimation model was applied to a validation period from January 2006 through March 2007, a period of 12 months of regional drought and base‐flow conditions followed by three months of above normal rainfall and a flood event. The model resulted in a Nash‐Sutcliffe estimation efficiency (E) of 0.45 for flow series (in log‐space) for the full 15‐month period, ?0.03 for the 2006 drought condition period, and 0.87 for the 2007 wet condition period. The overall model had a relative volume error of ?32%. The contribution of parameter uncertainties to model discrepancy was evaluated.     

MODELING ACTUAL EVAPOTRANSPIRATION FROM FORESTED WATERSHEDS ACROSS THE SOUTHEASTERN UNITED STATES1

ABSTRACT: About 50 to 80 percent of precipitation in the southeastern United States returns to the atmosphere by evapotranspiration. As evapotranspiration is a major component in the forest water balances, accurately quantifying it is critical to predicting the effects of forest management and global change on water, sediment, and nutrient yield from forested watersheds. However, direct measurement of forest evapotranspiration on a large basin or a regional scale is not possible. The objectives of this study were to develop an empirical model to estimate long‐term annual actual evapotranspiration (ART) for forested watersheds and to quantify spatial AET patterns across the southeast. A geographic information system (GIS) database including land cover, daily streamflow, and climate was developed using long term experimental and monitoring data from 39 forested watersheds across the region. Using the stepwise selection method implemented in a statistical modeling package, a long term annual AET model was constructed. The final multivariate linear model includes four independent variables—annual precipitation, watershed latitude, watershed elevation, and percentage of forest coverage. The model has an adjusted R² of 0.794 and is sufficient to predict long term annual ART for forested watersheds across the southeastern United States. The model developed by this study may be used to examine the spatial variability of water availability, estimate annual water loss from mesoscale watersheds, and project potential water yield change due to forest cover change.     

Neural Network Input Selection for Hydrological Forecasting Affected by Snowmelt1

Abstract: Snowmelt largely affects runoff in watersheds in Nordic countries. Neural networks (NN) are particularly attractive for streamflow forecasting whereas they rely at least on daily streamflow and precipitation observations. The selection of pertinent model inputs is a major concern in NNs implementation. This study investigates performance of auxiliary NN inputs that allow short‐term streamflow forecasting without resorting to a deterministic snowmelt routine. A case study is presented for the Rivière des Anglais watershed (700 km²) located in Southern Québec, Canada. Streamflow (Q), precipitations (rain R and snow S, or total P), temperature (T) and snow lying (A) observations, combined with climatic and snowmelt proxy data, including snowmelt flow (Q_SM) obtained from a deterministic model, were tested. NN implemented with antecedent Q and R produced the largest gains in performance. Introducing increments of A and T to the NNs further improved the performance. Long‐term averages, seasonal data, and Q_SM failed to improve the networks.     

Multiscale Analysis of Hydrology in a Mountaintop Mine‐Impacted Watershed

In the Appalachian region of the eastern United States, mountaintop removal mining (MTM) is a dominant driver of land‐cover change, impacting 6.8% of the largely forested 4.86 million ha coal fields region. Recent catastrophic flooding and documented biological impairment downstream of MTM has drawn sharp criticism to this practice. Despite its extent, scale, and use since the 1970s, the impact of MTM on hydrology is poorly understood. Therefore, the goal of this study was a multiscale evaluation to establish the nature of hydrologic impacts associated with MTM. To quantify the extent of MTM, land‐cover change over the lifetime of this practice is estimated for a mesoscale watershed in southern West Virginia. To assess hydrologic impacts, we conducted long‐term trend analyses to evaluate for systematic changes in hydrology at the mesoscale, and conducted hydrometric and response time modeling to characterize storm‐scale responses of a MTM‐impacted headwater catchment. Results show a general trend in the conversion of forests to mines, and significant decreases in maximum streamflow and variability, and increases in base‐flow ratio attributed to valley fills and deep mine drainage. Decreases in variability are shown across spatial and temporal scales having important implications for water quantity and quality. However, considerable research is necessary to understand how MTM impacts hydrology. In an effort to inform future research, we identify existing knowledge gaps and limitations of our study.     

APPLICATION OF THE RHESSys MODEL TO A CALIFORNIA SEMIARID SHRUBLAND WATERSHED1

ABSTRACT: Distributed hydrologic models which link seasonal streamflow and soil moisture patterns with spatial patterns of vegetation are important tools for understanding the sensitivity of Mediterranean type ecosystems to future climate and land use change. RHESSys (Regional Hydro‐Ecologic Simulation System) is a coupled spatially distributed hydroecological model that is designed to be able to represent these feedbacks between hydrologic and vegetation carbon and nutrient cycling processes. However, RHESSys has not previously been applied to semiarid shrubland watersheds. In this study, the hydrologic submodel of RHESSys is evaluated by comparing model predictions of monthly and annual streamflow to stream gage data and by comparing RHESSys behavior to that of another hydrologic model of similar complexity, MIKESHE, for a 34 km² watershed near Santa Barbara, California. In model intercomparison, the differences in predictions of temporal patterns in streamflow, sensitivity of model predictions to calibration parameters and landscape representation, and differences in model estimates of soil moisture patterns are explored. Results from this study show that both models adequately predict seasonal patterns of streamflow response relative to observed data, but differ significantly in terms of estimates of soil moisture patterns and sensitivity of those patterns to the scale of landscape tessellation used to derive spatially distributed elements. This sensitivity has implications for implementing RHESSys as a tool to investigate interactions between hydrology and ecosystem processes.     

Precipitation as the Primary Driver of Variability in River Nitrogen Loads in the Midwest United States

Nitrogen (N) losses from agricultural lands in the Midwest United States are contributing to the expansion of the hypoxic zone in the Gulf of Mexico. This study evaluated the importance of inter‐annual variability in precipitation, land cover, and N fertilizer use on NO₃ + NO₂‐N loads in seven United States Midwestern Rivers using the backward stepwise regression analysis. At the annual scale, fluctuations in the current and previous years’ precipitations explained much of the variation in streamflow, baseflow, and N‐load. Previous years precipitation effects were associated with fillable soil porosity. In some years, higher residual soil N from previous dry years also contributed to an increase in N‐load. Area under soybean production (SOY), a surrogate for replacement of prairies and small grains was generally not a significant explanatory variable. Fertilizer use from 1987 to 2012 was also not a significant explanatory variable in the annual analysis. Precipitation in both the current and previous months and previous year were important in explaining variation in monthly streamflow, baseflow, and N‐load. SOY was significant in one or two months from June to August, but had a higher p‐value than precipitation. We conclude recent increases in river N‐loads are primarily due to wet climate and minimally due to the changes in land cover or N fertilizer use. Under current cropping systems and agronomic N application rates, tile water remediation will be necessary to reduce river N‐loads.     

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.     

Land-Use Systems and Resilience of Tropical Rain Forests in the Tehuantepec Isthmus,Mexico

Land-cover types were analyzed for 1970, 1990 and 2000 as the bases for determining land-use systems and their influence on the resilience of tropical rain forests in the Tehuantepec Isthmus, Mexico. Deforestation (DR) and mean annual transformation rates were calculated from land-cover change data; thus, the classification of land-use change processes was determined according to their impact on resilience: a) Modification, including land-cover conservation and intensification, and b) Conversion, including disturbance and regeneration processes. Regeneration processes, from secondary vegetation under extensive use, cultivated vegetation under intensive use, and cultivated or induced vegetation under extensive use to mature or secondary vegetation, have high resilience capacity. In contrast, cattle-raising is characterized by rapid expansion, long-lasting change, and intense damages; thus, recent disturbance processes, which include the conversion to cattle-raising, provoke the downfall of the traditional agricultural system, and nullify the capacity of resilience of tropical rain forest. The land-use cover change processes reveal a) the existence of four land-use systems (forestry, extensive agriculture, extensive cattle-raising, and intensive uses) and b) a trend towards the replacement of agricultural and forestry systems by extensive cattle-raising, which was consolidated during 1990–2000 (DR of evergreen tropical rain forest=4.6%). Only the forestry system, which is not subject to deforestation, but is affected by factors such as selective timber, extraction, firewood collection, grazing, or human-induced fire, is considered to have high resilience (2 years), compared to agriculture (2–10 years) or cattle-raising (nonresilient). It is concluded that the analysis of land-use systems is essential for understanding the implications of land-use cover dynamics on forest recovery and land degradation in tropical rain forests.     

FORESTS AND OTHER FACTORS ASSOCIATED WITH STREAMFLOWS IN EAST TEXAS1

Effects of proportion of watersheds in forest and watershed physiographic factors on mean annual streamflow (1965-76), median flow, and 12 flood flow characteristics were regionally analyzed for 19 unregulated streams in East Texas. Annual streamflow increased with decreasing proportion of forest area. Differences in annual streamflow between full forest cover and bare watersheds could be as much as 200 mm. Other things being equal, the minimum watershed area required to generate 0.142 cm (5 cfs), a criterion used by the U.S. Corps of Engineering in regulating dredge and fill activity for water pollution abatement in East Texas streams, is 70 km² (27 mi²). Of the 31 physio-climatic parameters analyzed, watershed area, percent forest area, shape index, spring precipitation, and annual temperature were the most significant in affecting streamflow characteristics in East Texas. Using 2-3 of these five variables, all of the 14 streamflow characteristics can be estimated with accuracy ranging from acceptable to excellent levels.     

Constraining SWAT Calibration with Remotely Sensed Evapotranspiration Data

Historically, many watershed studies have been based on using the streamflow flux, typically from a single gauge at the basin's outlet, to support calibration. In this setting, there is great potential for equifinality of parameters during the optimization process, especially for parameters that are not directly related to streamflow. Therefore, some of the optimal parameter values achieved during the autocalibration process may be physically unrealistic. In recent decades a vast array of data from land surface models and remote sensing platforms can help to constrain hydrologic fluxes such as evapotranspiration (ET). While the spatial resolution of these ancillary datasets varies, the continuous spatial coverage of these gridded datasets provides flux measurements across the entire basin, in stark contrast to point‐based streamflow data. This study uses Global Land Evaporation: the Amsterdam Model data to constrain Soil and Water Assessment Tool parameter values associated with ET to a more physically realistic range. The study area is the Little Washita River Experimental Watershed, in southern Oklahoma. Traditional objective metrics such as the Nash‐Sutcliffe coefficients record no performance improvement after application of this method. However, there is a dramatic increase in the number of days with receding flow where simulations match observed streamflow.     

Analysis of Spatial and Temporal Evolution of Vegetation Cover in the Spanish Central Pyrenees: Role of Human Management

A vegetation cover increase has been identified at global scales using satellite images and vegetation indices. This fact is usually explained by global climatic change processes such as CO₂ and temperature increases. Nevertheless, although these causes can be important, the role of socioeconomic transformations must be considered in some places, since in several areas of Northern Hemisphere an important change in management practices has been detected. Rural depopulation and land abandonment have reactivated the natural vegetation regeneration processes. This work analyses the vegetation evolution in the central Spanish Pyrenees from 1982 to 2000. The analysis has been done by using calibrated-NDVI temporal series from NOAA-AVHRR images. A positive and significant trend in NDVI data has been identified from 1982 to 2000 coinciding with a temperature increase in the study area. However, the spatial differences in magnitude and the sign of NDVI trends are significant. The role of land management changes in the 20th century is considered as a hypothesis to explain the spatial differences in NDVI trends. The role of land-cover and human land-uses on this process has been analyzed. The highest increment of NDVI is detected in lands affected by abandonment and human extensification. The importance of management changes in vegetation growth is discussed, and we indicate that although climate has great importance in vegetal evolution, land-management changes can not be neglected in our study area.     

Water Balances of Two Piedmont Headwater Catchments: Implications for Regional Hydrologic Landscape Classification

In the Piedmont of North Carolina, a traditionally water‐rich region, reservoirs that serve over 1 million people are under increasing pressure due to naturally occurring droughts and increasing land development. Innovative development approaches aim to maintain hydrologic conditions of the undisturbed landscape, but are based on insufficient target information. This study uses the hydrologic landscape concept to evaluate reference hydrology in small headwater catchments surrounding Falls Lake, a reservoir serving Raleigh and the greater Triangle area. Researchers collected one year of detailed data on water balance components, including precipitation, evapotranspiration, streamflow, and shallow subsurface storage from two headwater catchments representative of two hydrologic landscapes defined by differences in soils and topographic characteristics. The two catchments are similar in size and lie within the same physiographic region, and during the study period they showed similar water balances of 26‐30% Q, ?4 to 5% ΔS, 59‐65% evapotranspiration, and 9‐10% G. However, the steeper, more elevated catchment exhibited perennial streamflow and nongrowing season runoff ratios (Q/P) of 33%, whereas the flat, low‐lying stream was drier during the growing season and exhibited Q/P ratios of 52% during the nongrowing season. A hydrologic landscape defined by topography and soil characteristics helps characterize local‐scale reference hydrology and may contribute to better land management decisions.