David C. Goodrich

Integration of soil moisture remote sensing and hydrologic modeling using data assimilation

The feasibility of synthesizing distributed fields of soil moisture by the novel application of four-dimensional data assimilation (4DDA) applied in a hydrological model is explored. Six 160-km2 push broom microwave radiometer (PBMR) images gathered over the Walnut Gulch experimental watershed in southeast Arizona were assimilated into the Topmodel-based Land-Atmosphere Transfer Scheme (TOPLATS) using several alternative assimilation procedures. Modification of traditional assimilation methods was required to use these high-density PBMR observations. The images were found to contain horizontal correlations that imply length scales of several tens of kilometers, thus allowing information to be advected beyond the area of the image. Information on surface soil moisture also was assimilated into the subsurface using knowledge of the surface- subsurface correlation. Newtonian nudging assimilation procedures are preferable to other techniques because they nearly preserve the observed patterns within the sampled region but also yield plausible patterns in unmeasured regions and allow information to be advected in time.

Validation of Advanced Microwave Scanning Radiometer Soil Moisture Products

Validation is an important and particularly challenging task for remote sensing of soil moisture. A key issue in the validation of soil moisture products is the disparity in spatial scales between satellite and in situ observations. Conventional measurements of soil moisture are made at a point, whereas satellite sensors provide an integrated area/volume value for a much larger spatial extent. In this paper, four soil moisture networks were developed and used as part of the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) validation program. Each network is located in a different climatic region of the U.S., and provides estimates of the average soil moisture over highly instrumented experimental watersheds and surrounding areas that approximate the size of the AMSR-E footprint. Soil moisture measurements have been made at these validation sites on a continuous basis since 2002, which provided a seven-year period of record for this analysis. The National Aeronautics and Space Administration (NASA) and Japan Aerospace Exploration Agency (JAXA) standard soil moisture products were compared to the network observations, along with two alternative soil moisture products developed using the single-channel algorithm (SCA) and the land parameter retrieval model (LPRM). The metric used for validation is the root-mean-square error (rmse) of the soil moisture estimate as compared to the in situ data. The mission requirement for accuracy defined by the space agencies is 0.06 m3/m3. The statistical results indicate that each algorithm performs differently at each site. Neither the NASA nor the JAXA standard products provide reliable estimates for all the conditions represented by the four watershed sites. The JAXA algorithm performs better than the NASA algorithm under light-vegetation conditions, but the NASA algorithm is more reliable for moderate vegetation. However, both algorithms have a moderate to large bias in all cases. The SCA had the lowest overall rmse with a small bias. The LPRM had a very large overestimation bias and retrieval errors. When site-specific corrections were applied, all algorithms had approximately the same error level and correlation. These results clearly show that there is much room for improvement in the algorithms currently in use by JAXA and NASA. They also illustrate the potential pitfalls in using the products without a careful evaluation.

Impact of small-scale spatial rainfall variability on runoff modeling

Rainfall and wind data obtained from a dense raingage network on a 4.4 ha semiarid catchment were used as input to a distributed rainfall-runoff model. It was shown that the wind direction and velocity have a relatively small impact on peak rate and runoff volume for this low relief watershed. However, even at this small scale, spatial variability of precipitation can translate into large variations in modeled runoff. When five model runs were conducted using input from one of five recording raingages, one at a time, the coefficient of variation for peak rate and runoff volume ranged from 9 to 76%, and from 2 to 65%, respectively, over eight observed storm events. By using four well distributed gages the variations in modeled runoff volume approach the sampling resolution of the raingages as well as the estimated accuracy of runoff volume and peak rate observations. The results of this study indicate that if distributed catchment modeling is to be conducted at the 5 ha scale in an environment dominated by convective air-mass thunderstorm rainfall, knowledge of the spatial rainfall variability on the same scale is required. A single raingage with the standard uniform rainfall assumption can lead to large uncertainties in runoff estimation.

Validation of Soil Moisture and Ocean Salinity (SMOS) Soil Moisture Over Watershed Networks in the U.S.

Estimation of soil moisture at large scale has been performed using several satellite-based passive microwave sensors and a variety of retrieval methods over the past two decades. The most recent source of soil moisture is the European Space Agency Soil Moisture and Ocean Salinity (SMOS) mission. A thorough validation must be conducted to insure product quality that will, in turn, support the widespread utilization of the data. This is especially important since SMOS utilizes a new sensor technology and is the first passive L-band system in routine operation. In this paper, we contribute to the validation of SMOS using a set of four in situ soil moisture networks located in the U.S. These ground-based observations are combined with retrievals based on another satellite sensor, the Advanced Microwave Scanning Radiometer (AMSR-E). The watershed sites are highly reliable and address scaling with replicate sampling. Results of the validation analysis indicate that the SMOS soil moisture estimates are approaching the level of performance anticipated, based on comparisons with the in situ data and AMSR-E retrievals. The overall root-mean-square error of the SMOS soil moisture estimates is 0.043 m3/m3 for the watershed networks (ascending). There are bias issues at some sites that need to be addressed, as well as some outlier responses. Additional statistical metrics were also considered. Analyses indicated that active or recent rainfall can contribute to interpretation problems when assessing algorithm performance, which is related to the contributing depth of the satellite sensor. Using a precipitation flag can improve the performance. An investigation of the vegetation optical depth (tau) retrievals provided by the SMOS algorithm indicated that, for the watershed sites, these are not a reliable source of information about the vegetation canopy. The SMOS algorithms will continue to be refined as feedback from validation is evaluated, and it is expected that the SMOS estimates will improve.

Linearity of basin response as a function of scale in a semiarid watershed

Linearity of basin runoff and peak response as a function of watershed scale was examined for a set of 29 nested semiarid watersheds within the U.S. Department of Agriculture–Agricultural Research Service Walnut Gulch Experimental Watershed, located in southeastern Arizona. Watershed drainage areas range from 1.83 × 103 to 1.48 × 108 m2 (0.183–14800 ha), and all stream channels are ephemeral. Observations of mean annual runoff, database-derived 2- and 100-year peak runoff rates, ephemeral channel area, and areal rainfall characteristics derived from 304 events were examined to assess the nature of runoff response behavior over this range of watershed scales. Two types of distributed rainfall-runoff models of differing complexity were applied to a subset of the watersheds to further investigate the scale-dependent nature of the collected data. Contrary to the conclusions of numerous studies in more humid regions, it was found that watershed runoff response becomes more nonlinear with increasing watershed scale, with a critical transition threshold area occurring roughly around the range of 3.7 × 105 to 6.0 × 105 m2 (37–60 ha). The primary causes of increasingly nonlinear response are the increasing importance of ephemeral channel losses and partial storm area coverage. The modeling results indicate that significant error will result in model estimates of peak runoff rates when rainfall inputs from depth area-frequency relationships are applied beyond the area of typical storm coverage. For runoff modeling in Walnut Gulch and similar semiarid environments, explicit treatment of channel routing and transmission losses from channel infiltration will be required for watersheds larger than the critical drainage area.

Measurement and analysis of small-scale convective storm rainfall variability

Abstract For large-scale catchment hydrology, the crucial importance of a good estimate of spatial rainfall variability is generally admitted. However, the assumption of uniform rainfall is still applied for small areas, whether they are studied as individual catchments or represent an elementary area in a distributed model. To investigate the validity of this assumption, an experiment was conducted in a small catchment (4.4 ha) in the semiarid USDA-ARS Walnut Gulch Experimental Watershed. Measurements were made with recording and non-recording raingages as well as vectopluviometers for a range of events during the 1990 monsoon season (July–September). Geostatistical analysis of the data indicated the presence of first-order drift with corresponding rainfall gradients ranging from 0.28 to 2.48 mm per 100 m with an average of 1.2 mm per 100 m. These gradients represent a 4–14% variation of the mean rainfall depth over a 100 m distance. Given these observations, the assumption of spatial rainfall uniformity in this and similar convective environments at the small watershed scale of 5 ha appears to be invalid.

Combining the Penman-Monteith equation with measurements of surface temperature and reflectance to estimate evaporation rates of semiarid grassland

The Penman-Monteith equation is useful for computing evaporation rates of uniform surfaces, such as dense vegetation or bare soil. This equation becomes less useful for evaluation of evaporation rates at the regional scale, where surfaces are generally characterized by a patchy combination of vegetation and soil. This is particularly true in the arid and semi-arid regions of the world. The approach proposed here is an attempt to use remotely-sensed measurements of surface reflectance and temperature to allow application of the Penman-Monteith theory to partiallyvegetated fields without a-priori knowledge of the percent vegetation cover and canopy resistance. Basically, the Penman-Monteith equation was combined with the energy balance equation to estimate the surface temperature CT,) associated with four states: surfaces characterized by full-cover vegetation and bare soil with evaporation rates at potential and zero. Then, linear interpolations between T, values computed for full-cover and bare soil conditions were used to provide information at intermediate states based on measurements of actual surface reflectance and temperature. The approach was first tested using ground-based measurements of surface reflectance and temperature at a rangeland site; the results compared well with on-site measure

The Automated Geospatial Watershed Assessment tool

A toolkit for distributed hydrologic modeling at multiple scales using two independent models within a geographic information system is presented. This open-source, freely available software was developed through a collaborative endeavor involving two Universities and two government agencies. Called the Automated Geospatial Watershed Assessment tool (AGWA), this software is written for the ArcView GIS platform and is distributed as an extension via the Internet. AGWA uses commonly available GIS data layers to fully parameterize, execute, and visualize results from both the Soil and Water Assessment Tool (SWAT) and Kinematic Runoff and Erosion model (KINEROS2). These two distributed hydrologic models operate at different time scales and are suitable for application across a range of spatial scales. Descriptions of the GIS framework, hydrologic models, spatial analyses and algorithms that control the modeling process are given. Model requirements, limitations on the model applications and calibration techniques are described with examples of the use of AGWA for watershed modeling and assessment at a range of scales. 2006 Elsevier Ltd. All rights reserved.

Modeling runoff response to land cover and rainfall spatial variability in semi-arid watersheds.

Hydrologic response is an integrated indicator of watershed condition, and significant changes in land cover may affect the overall health and function of a watershed. This paper describes a procedure for evaluating the effects of land cover change and rainfall spatial variability on watershed response. Two hydrologic models were applied on a small semi-arid watershed; one model is event-based with a one-minute time step (KINEROS), and the second is a continuous model with a daily time step (SWAT). The inputs to the models were derived from Geographic Information System (GIS) theme layers of USGS digital elevation models, the State Soil Geographic Database (STATSGO) and the Landsat-based North American Landscape Characterization classification (NALC) in conjunction with available literature and look up tables. Rainfall data from a network of 10 raingauges and historical stream flow data were used to calibrate runoff depth using the continuous hydrologic model from 1966 to 1974. No calibration was carried out for the event-based model, in which six storms from the same period were used in the calculation of runoff depth and peak runoff. The assumption on which much of this study is based is that land cover change and rainfall spatial variability affect the rainfall-runoff relationships on the watershed. To validate this assumption, simulations were carried out wherein the entire watershed was transformed from the 1972 NALC land cover, which consisted of a mixture of desertscrub and grassland, to a single uniform land cover type such as riparian, forest, oak woodland, mesquite woodland, desertscrub, grassland, urban, agriculture, and barren. This study demonstrates the feasibility of using widely available data sets for parameterizing hydrologic simulation models. The simulation results show that both models were able to characterize the runoff response of the watershed due to changes of land cover.

Seasonal estimates of riparian evapotranspiration using remote and in situ measurements

In many semi-arid basins during extended periods when surface snowmelt or storm runoff is absent, groundwater constitutes the primary water source for human habitation, agriculture and riparian ecosystems. Utilizing regional groundwater models in the management of these water resources requires accurate estimates of basin boundary conditions. A critical groundwater boundary condition that is closely coupled to atmospheric processes and is typically known with little certainty is seasonal riparian evapotranspiration (ET). This quantity can often be a significant factor in the basin water balance in semi-arid regions yet is very difficult to estimate over a large area. Better understanding and quantification of seasonal, large-area riparian ET is a primary objective of the Semi-Arid Land-Surface-Atmosphere (SALSA) Program. To address this objective, a series of interdisciplinary experimental campaigns were conducted in 1997 in the San Pedro Basin in southeastern Arizona. The riparian system in this basin is primarily made up of three vegetation communities: mesquite (Prosopis velutina), sacaton grasses (Sporobolus wrightii), and a cottonwood (Populus fremontii)/willow (Salix goodingii) forest gallery. Micrometeorological measurement techniques were used to estimate ET from the mesquite and grasses. These techniques could not be utilized to estimate fluxes from the cottonwood/willow (C/W) forest gallery due to the height (20‐30 m) and non-uniform linear nature of the forest gallery. Short-term (2‐4 days) sap flux measurements were made to estimate canopy transpiration over several periods of the riparian growing season. Simultaneous remote sensing measurements were used to spatially extrapolate tree and stand measurements. Scaled C/W stand level sap flux estimates were utilized to calibrate a Penman‐Monteith model to enable temporal extrapolation between synoptic measurement periods. With this model and set of measurements, seasonal riparian vegetation water use estimates for the riparian corridor were obtained. To validate these models, a 90-day pre-monsoon water balance over a 10 km section of the river was carried out. All components of the water balance, including riparian ET, were