Land Surface Water Balance Research Articles

Climate Prediction Center global monthly soil moisture data set at 0.5° resolution for 1948 to present

We have produced a 0.5° × 0.5° monthly global soil moisture data set for the period from 1948 to the present. The land model is a one‐layer “bucket” water balance model, while the driving input fields are Climate Prediction Center monthly global precipitation over land, which uses over 17,000 gauges worldwide, and monthly global temperature from global Reanalysis. The output consists of global monthly soil moisture, evaporation, and runoff, starting from January 1948. A distinguishing feature of this data set is that all fields are updated monthly, which greatly enhances utility for near‐real‐time purposes. Data validation shows that the land model does well; both the simulated annual cycle and interannual variability of soil moisture are reasonably good against the limited observations in different regions. A data analysis reveals that, on average, the land surface water balance components have a stronger annual cycle in the Southern Hemisphere than those in the Northern Hemisphere. From the point of view of soil moisture, climates can be characterized into two types, monsoonal and midlatitude climates, with the monsoonal ones covering most of the low‐latitude land areas and showing a more prominent annual variation. A global soil moisture empirical orthogonal function analysis and time series of hemisphere means reveal some interesting patterns (like El Niño‐Southern Oscillation) and long‐term trends in both regional and global scales.

Soil moisture–temperature relationships: results from two field experiments

AbstractThis paper analyses data from two field experiments in Chickasha, Oklahoma, and Tifton, Georgia, carried out in July 1999 and June 2000 respectively. The observations on soil moisture at two depths, viz. 0–2·5 and 0–5·0 cm, surface temperature, and temperatures at 1, 5 and 10 cm depths are analysed. The relationship between the soil moisture and the temperature variability in time is examined as a function of vegetation type and location. Results from these experiments show that, during drydown, surface temperature shows an increase that corresponds to a decrease in the soil moisture. Linear models for prediction of soil moisture (at both depths) using surface temperature observations are examined. Copyright © 2003 John Wiley & Sons, Ltd.

The role of surface storage in a low‐gradient Arctic watershed

The Arctic land surface water balance plays an important role in regulating the planetary heat balance and global ocean circulation. Lakes and wetlands are common features in the low‐gradient Putuligayuk River watershed in northern Alaska, with important implications for the annual water balance. Evapotranspiration exceeds precipitation over the summer, and there is a gradual reduction in wetland extent. Total inundated area derived from RADARSAT ScanSAR synthetic aperture radar images throughout 1999 and 2000 varied from 15 to 67 percent of the 471 km2 watershed. The hydrological system becomes disconnected within 2 weeks of snowmelt, and overland flow largely ceases. End‐of‐winter snow water equivalent and discharge during the melt period for 1999, 2000, and 2001 were used to estimate that between 30 and 37 mm (24–42 percent) of snow meltwater serves to recharge the evaporation deficit of the previous summer. The percent of snowmelt entering storage is dependent on the available surface storage.

Sensitivity, spatial heterogeneity, and scaling of C-band microwave brightness temperatures for land hydrology studies

Soil moisture is one of the most important hydrological variables that characterizes the land surface water and energy balance. Measurements from space suffer from the problem of subpixel heterogeneity, i.e., soil moisture has spatial variability at all scales; therefore, it is important to realize the exact physical implication of the single value of the satellite measurements. In this paper, we study the sensitivity of C-band passive microwave brightness temperatures to various land surface variables. The issue of heterogeneity and its role in interpretation of single spatially averaged value of satellite brightness temperature is investigated. Finally, we use the brightness temperatures from the Scanning Multichannel Microwave Radiometer to characterize spatial variability and to understand the variation of this variability with scale.

A Long-Term Hydrologically Based Dataset of Land Surface Fluxes and States for the Conterminous United States*

A frequently encountered difficulty in assessing model-predicted land–atmosphere exchanges of moisture and energy is the absence of comprehensive observations to which model predictions can be compared at the spatial and temporal resolutions at which the models operate. Various methods have been used to evaluate the land surface schemes in coupled models, including comparisons of model-predicted evapotranspiration with values derived from atmospheric water balances, comparison of model-predicted energy and radiative fluxes with tower measurements during periods of intensive observations, comparison of model-predicted runoff with observed streamflow, and comparison of model predictions of soil moisture with spatial averages of point observations. While these approaches have provided useful model diagnostic information, the observation-based products used in the comparisons typically are inconsistent with the model variables with which they are compared—for example, observations are for points or areas much smaller than the model spatial resolution, comparisons are restricted to temporal averages, or the spatial scale is large compared to that resolved by the model. Furthermore, none of the datasets available at present allow an evaluation of the interaction of the water balance components over large regions for long periods. In this study, a model-derived dataset of land surface states and fluxes is presented for the conterminous United States and portions of Canada and Mexico. The dataset spans the period 1950–2000, and is at a 3-h time step with a spatial resolution of ⅛ degree. The data are distinct from reanalysis products in that precipitation is a gridded product derived directly from observations, and both the land surface water and energy budgets balance at every time step. The surface forcings include precipitation and air temperature (both gridded from observations), and derived downward solar and longwave radiation, vapor pressure deficit, and wind. Simulated runoff is shown to match observations quite well over large river basins. On this basis, and given the physically based model parameterizations, it is argued that other terms in the surface water balance (e.g., soil moisture and evapotranspiration) are well represented, at least for the purposes of diagnostic studies such as those in which atmospheric model reanalysis products have been widely used. These characteristics make this dataset useful for a variety of studies, especially where ground observations are lacking.

Multiobjective calibration and sensitivity of a distributed land surface water and energy balance model

The feasibility of using spatially distributed information to improve the predictive ability of a spatially distributed land surface water and energy balance model (LSM) was explored at the U.S. Department of Agriculture Agricultural Research Service (USDA‐ARS) Walnut Gulch Experimental Watershed in southeastern Arizona. The inclusion of spatially variable soil and vegetation information produced unrealistic simulations that were inconsistent with observations, which was likely an artifact of both discretely assigning a single set of parameters to a given area and inadequate knowledge of spatially varying parameter values. Because some of the model parameters were not measured or are abstract quantities a multiobjective least squares strategy was used to find catchment averaged parameter values that minimize the prediction error of latent heat flux, soil heat flux, and surface soil moisture. This resulted in a substantial improvement in the model's spatially distributed performance and yielded valuable insights into the interaction and optimal selection of model parameters.

Surface water balance of the continental United States, 1963–1995: Regional evaluation of a terrestrial biosphere model and the NCEP/NCAR reanalysis

The land surface water balance of the continental United States is analyzed from 1963 to 1995 using a terrestrial biosphere model (IBIS), reanalysis data from NCEP/NCAR, a hydrologic routing model (HYDRA), and numerous observational data sets. Emphasis is placed on evaluating the performance of IBIS and the reanalysis, particularly over the central United States. IBIS is forced with daily climatic inputs from NCEP; an additional simulation is performed using observed precipitation. The NCEP reanalysis is found to have excessive precipitation and evapotranspiration over the central United States (particularly in the summertime), an exaggerated seasonal cycle of runoff, and low snow depths. The net surface water balance exhibits a dry bias that is corrected by nudging soil moisture toward climatology. Unfortunately, this correction term is large and appears to have a detrimental impact on other water balance components (particularly runoff). Fields that are reasonably well simulated in the reanalysis include fall and winter precipitation over the central United States, soil moisture in Illinois, and interannual variations in runoff. Results from the IBIS simulations show generally better agreement with observations than the NCEP reanalysis but continue to have nontrivial errors in certain fields. Over the central United States, these discrepancies include high winter/spring evapotranspiration (1 mm d−1 too high), low snow depth, and weak spring runoff (30–50% too low). The errors are at least partially caused by underestimated cloud cover and early spring green‐up. A spatial analysis of the U.S. water balance reveals that some of the strongest seasonal and interannual variations in precipitation, evapotranspiration, and soil moisture occur over the central United States.

Global pattern of potential evaporation calculated from the Penman-Monteith equation using satellite and assimilated data

Potential evaporation has been used to provide a reference level for actual evaporation in many studies of land surface heat and water balance. While Thornthwaite's formula has been used in many regional and global studies, the Penman-Monteith equation has been shown to provide an accurate estimate of this evaporation. Thus, global pattern of potential evaporation has been caleulated from the Penman-Monteith equation using satellite and assimilated data for a 24-month period, January 1987 to December 1988. The albedo and surface resistance have been taken to be, respectively, 0.23 and 70 s m −1, which are considered to be representative values for actively growing well-watered grass covering the ground. Satellite observations have been used to obtain spatially representative monthly values of solar radiation, fractional cloud cover, air temperature, and vapor pressure, while aerodynamic resistance has been calculated using four-dimensional data assimilation results. Meteorologic data derived from satellite observations are compared with the surface (station) measurements. The calculated potential evaporation values are compared with lysimeter observations for evaporation from well-watered grass at 35 widely distributed locations in different climatic regimes to quantify the accuracy of the calculated values. The evaporation values have been archived for distribution. http://hydro4.gsfc.nasa.gov/STAFF/ChoudhuryBj/pmpotevap.html.

Timescales of Land Surface Evapotranspiration Response

Abstract Soil and vegetation exert strong control over the evapotranspiration rate, which couples the land surface water and energy balances. A method is presented to quantify the timescale of this surface control using daily general circulation model (GCM) simulation values of evapotranspiration and precipitation. By equating the time history of evaporation efficiency (ratio of actual to potential evapotranspiration) to the convolution of precipitation and a unit kernel (temporal weighting function), response functions are generated that can be used to characterize the timescales of evapotranspiration response for the land surface model (LSM) component of GCMs. The technique is applied to the output of two multiyear simulations of a GCM, one using a Surface-Vegetation-Atmosphere-Transfer (SVAT) scheme and the other a Bucket LSM. The derived response functions show that the Bucket LSM’s response is significantly slower than that of the SVAT across the globe. The analysis also shows how the timescales of i...

Sensitivity of greenhouse summer dryness to changes in plant rooting characteristics

A possible consequence of increased concentrations of greenhouse gases in Earth's atmosphere is “summer dryness,” a decrease of summer plant‐available soil water in middle latitudes, caused by increased availability of energy to drive evapotranspiration. Results from a numerical climate model indicate that summer dryness and related changes of land‐surface water balances are highly sensitive to possible concomitant changes of plant‐available water‐holding capacity of soil, which depends on plant rooting depth and density. The model suggests that a 14% decrease of the soil volume whose water is accessible to plant roots would generate the same summer dryness, by one measure, as an equilibrium doubling of atmospheric carbon dioxide. Conversely, a 14% increase of that soil volume would be sufficient to offset the summer dryness associated with carbon‐dioxide doubling. Global and regional changes in rooting depth and density may result from (1) plant and plant‐community responses to greenhouse warming, to carbon‐dioxide fertilization, and to associated changes in the water balance and (2) anthropogenic deforestation and desertification. Given their apparently critical role, heretofore ignored, in global hydroclimatic change, such changes of rooting characteristics should be carefully evaluated using ecosystem observations, theory, and models.

FIFE 1987 water budget analysis

The First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE) represents one of the largest data collection campaigns to date in our endeavor to observe the hydrodynamic and thermodynamic processes occurring on the land surface of the Earth. Data for FIFE have been widely used to improve our understanding of land surface processes and to improve the representation of the land surface and boundary layer in atmospheric models. Because FIFE data are being used to test models of land surface processes, it is important to examine how well the FIFE data preserve the water budget. Therefore this study examined the data consistency issue from a hydrologic perspective. More specifically, we investigated whether there is a consistent land surface water balance for the FIFE area over the 1987 experiment period. All components of water balance, i.e., rainfall, evaporation, runoff, and soil moisture, were examined individually as well as collectively. Gridded fields were made of each component. Both the gridded fields and areal averages were analyzed. The processed data were also compared with the data sets processed by other researchers. Inconsistencies in the data were pointed out and the sources were investigated. The results indicate that spatially averaged rainfall, fluxes, and soil moisture storage time series derived from the FIFE data close the water budget reasonably well. It is recommended that these data be used for future development and testing of models.

Evaluation of the effects of general circulation models' subgrid variability and patchiness of rainfall and soil moisture on land surface water balance fluxes

AbstractMany existing general circulation models (GCMs) use so‐called ‘bucket algorithms’ to represent land‐surface hydrology. Wood et al. (1992) presented a generalization of the simple bucket representation, based on their variable infiltration capacity (VIC) model. The VIC model, in essence, assumes a statistical distribution of bucket sizes within the grid square. In this way, it provides a simple, computationally efficient and yet physically realistic model of land‐surface hydrology. A preliminary attempt is made here, using this simple model, to evaluate the effects of the spatial variability of rainfall intensities and the resulting soil moisture within a hypothetical GCM grid square. Rainfall is assumed to be patchy, with only a fraction of the grid square being wetted by rainfall at any given time. Within the wetted area, however, rainfall is allowed to vary randomly in space. Evaporation during interstorm periods is estimated from the rest of the grid square by a simple non‐linear function of the available soil moisture. The soil moisture is also assumed to be patchy and spatially variable due to the antecedent rainfall that caused it. A number of simplifying assumptions have been made in the model about the redistribution of soil moisture at the end of storm and interstorm periods, and the effects of a vegetation canopy have been ignored. The model is applied, under a variety of conditions, to estimate the biases in the modelled water balance fluxes if the assumed spatial heterogeneity is neglected. The model is also used to simulate the long‐term water balance dynamics under assumed hypothetical storm and inter‐storm climatic inputs, to see how the steady‐state hydrological regime is affected by spatial variability. These simulations are relevant to current efforts towards developing simple parameterizations of land‐surface hydrology that explicitly incorporate subgrid heterogeneity.

Regional scale evaporation and the atmospheric boundary layer

Evaporation into the atmosphere is fundamental to the fields of hydrology, meteorology, and climatology. With evolving interest in regional and global hydrologic processes there is an increasing recognition of the importance of the study of evaporation and land surface water balances for length scales of the order of 10 km. To obtain regional scale fluxes of water vapor, heat, and momentum, it is important to understand transport in the atmospheric boundary layer (ABL), which is defined to be that part of the atmosphere directly influenced by the land surface. In this review we briefly summarize some current models of evaporation and the ABL and discuss new experimental and computational opportunities that may aid our understanding of evaporation at these larger scales. In particular, consideration is given to remote sensing of the atmosphere, computational fluid dynamics and the role numerical models can play in understanding land‐atmosphere interaction. These powerful modeling and measurement tools are allowing us to visualize and study spatial and temporal scales previously untouched, thereby increasing the opportunities to improve our understanding of land‐atmosphere interaction.

Regional and Seasonal Estimates of Fractional Storm Coverage Based on Station Precipitation Observations

Simulated climates using numerical atmospheric general circulation models (GCMs) have been shown to be highly sensitive to the fraction of GCM grid area assumed to be wetted during rain events. The model hydrologic cycle and land-surface water and energy balance are influenced by the parameter bar-kappa, which is the dimensionless fractional wetted area for GCM grids. Hourly precipitation records for over 1700 precipitation stations within the contiguous United States are used to obtain observation-based estimates of fractional wetting that exhibit regional and seasonal variations. The spatial parameter bar-kappa is estimated from the temporal raingauge data using conditional probability relations. Monthly bar-kappa values are estimated for rectangular grid areas over the contiguous United States as defined by the Goddard Institute for Space Studies 4 deg x 5 deg GCM. A bias in the estimates is evident due to the unavoidably sparse raingauge network density, which causes some storms to go undetected by the network. This bias is corrected by deriving the probability of a storm escaping detection by the network. A Monte Carlo simulation study is also conducted that consists of synthetically generated storm arrivals over an artificial grid area. It is used to confirm the bar-kappa estimation procedure and to test the nature of the bias and its correction. These monthly fractional wetting estimates, based on the analysis of station precipitation data, provide an observational basis for assigning the influential parameter bar-kappa in GCM land-surface hydrology parameterizations.

Development of Global Land Surface Evapotranspiration and Water Balance Data Sets.

The global data sets with half-degree resolution of monthly evapotranspiration and water balance were produced using simplified water balance model and published global data set. Results are compared with information obtained by previous investigations that used different data sets and analytical approaches. In general, the quantitative features of hydrologic regimes at the earth's surface are successfully simulated. The value of water balance components at the terrestrial area also agrees well with those obtained by Baumgartner and Reichel. Particularly, the good correlation (r=0.89-0.95) was obtained from the comparison results between the computed annual evapotranspiration and observed values. The comparison of the latitudinal distribution shows that the large amount of water surplus in 45°N-75°N and deficit in 10°S-30°S rather than those of Legates and Mather. On the other hand, the latitudinal distribution of annual evapotranspiration shows very similar, except in middle-high latitudes region. Preliminary results suggest possible solutions to the problem of the evaluation of national water resources using these developed data sets.

An event‐based simulation model of moisture and energy fluxes at a bare soil surface

Land surface energy and water balances can be calculated by solving the partial differential equations governing vertical water and heat flow in the soil. Solution methodologies relying on standard discretization procedures are computationally intensive and are therefore poorly suited for long‐term‐simulations or Monte‐Carlo simulations. As an alternative,a certain degree of accuracy may be forfeited in exchange for great reductions in computational effort by using an event‐based simulation model. Since it uses closed‐form solutions of the governing equations as basic building blocks, the event‐based model avoids most of the work associated with discretization. The use of time condensation and simplified soil moisture kinematics allows these closed‐form solutions to serve in continuous simulations under randomly varying forcing. A modified force‐restore model of soil temperature provides the necessary link between the energy and water balances. In comparison with finite element solutions of a detailed set of partial differential equations governing water and heat transport in soil, the event‐based model closely reproduced average energy and water balances and surface temperatures and decreased computational effort by a factor of at least a hundred.