Evaluating DEM source and resolution uncertainties in the Soil and Water Assessment Tool

DEMs as important input parameters of environmental risk assessment models are notable sources of uncertainties. To illustrate the effect of DEM grid size and source on model outputs, a widely used watershed management model, the Soil and Water Assessment Tool (SWAT), was applied with two newly available DEMs as inputs (i.e. ASTER GDEM Version 1, and SRTM Version 4.1). A DEM derived from 1:10,000 high resolution digital line graph (DLG) was used as a baseline for comparisons. Eleven resample resolutions, from 5 to 140?m, were considered to evaluate the impact of DEM resolution on SWAT outputs. Results from a case study in South-eastern China indicate that the SWAT predictions of total phosphorus and total nitrogen decreased substantially with coarser resample resolution. A slightly decreasing trend was found in the SWAT predicted sediment when DEMs were resampled to coarser resolutions. The SWAT predicted runoff was not sensitive to resample resolution. For different data sources, ASTER GDEM did not perform better than SRTM in SWAT simulations even it was provided with a smaller grid size and higher vertical accuracy. The predicted outputs based on ASTER GDEM and SRTM were similar, and much lower than the ones based on DLG. This study presents potential uncertainties introduced by DEM resolutions and data sources, and recommends strategies choosing DEMs based on research objects and maximum acceptable errors.     

Impact of grid resolution on the integrated and distributed response of a coupled surface–subsurface hydrological model for the des Anglais catchment,Quebec

Digital elevation models (DEMs) at different resolutions (180, 360, and 720 m) are used to examine the impact of different levels of landscape representation on the hydrological response of a 690‐km² catchment in southern Quebec. Frequency distributions of local slope, plan curvature, and drainage area are calculated for each grid size resolution. This landscape analysis reveals that DEM grid size significantly affects computed topographic attributes, which in turn explains some of the differences in the hydrological simulations. The simulations that are then carried out, using a coupled, process‐based model of surface and subsurface flow, examine the effects of grid size on both the integrated response of the catchment (discharge at the main outlet and at two internal points) and the distributed response (water table depth, surface saturation, and soil water storage). The results indicate that discharge volumes increase as the DEM is coarsened, and that coarser DEMs are also wetter overall in terms of water table depth and soil water storage. The reasons for these trends include an increase in the total drainage area of the catchment for larger DEM cell sizes, due to aggregation effects at the boundary cells of the catchment, and to a decrease in local slope and plan curvature variations, which in turn limits the capacity of the watershed to transmit water downslope and laterally. The results obtained also show that grid resolution effects are less pronounced during dry periods when soil moisture dynamics are mostly controlled by vertical fluxes of evaporation and percolation. Copyright © 2010 John Wiley & Sons, Ltd.     

EFFECT OF DIGITAL ELEVATION MODEL RESOLUTION ON EMPIRICAL ESTIMATION OF SOIL LOSS AND SEDIMENT TRANSPORT WITH GIS

The horizontal accuracy of topographic data represented by digital elevation model (DEM) resolution brings about uncertainties in landscape process modeling with raster GIS. This paper presents a study on the effect of topographic variability on cell-based empirical estimation of soil loss and sediment transport. An original DEM of 10m resolution for a case watershed was re-sampled to three realizations of higher grid sizes for a comparative examination. Equations based on the USLE are applied to the watershed to calculate soil loss from each cell and total sediment transport to streams. The study found that the calculated total soil loss from the watershed decreases with the increasing DEM resolution with a linear correlation as spatial variability is reduced by cell aggregation. The USLE topographic factors (LS) extracted from applied DEMs represent spatial variability, and determine the estimations as shown in the modeling results. The commonly used USGS 30m DEM appears to be able to reflect essential spatial variability and suitable for the empirical estimation. The appropriateness of a DEM resolution is dependent upon specific landscape characteristics, applied model and its parameterization. This work attempts to provide a general framework for the research in the DEM-based empirical modeling.     

The practice of DEM stream burning revisited

Stream burning is a common flow enforcement technique used to correct surface drainage patterns derived from digital elevation models (DEM). The technique involves adjusting the elevations of grid cells that are coincident with the features of a vector hydrography layer. This paper focuses on the problematic issues with common stream burning practices, particularly the topological errors resulting from the mismatched scales of the hydrography and DEM data sets. A novel alternative stream burning method is described and tested using five DEMs of varying resolutions (1 to 30 arc‐seconds) for an extensive area of southwestern Ontario, Canada. This TopologicalBreachBurn method uses total upstream channel length (TUCL) to prune the vector hydrography layer to a level of detail that matches the raster DEM grid resolution. Network pruning reduces the occurrence of erroneous stream piracy caused by the rasterization of multiple stream links to the same DEM grid cell. The algorithm also restricts flow within individual stream reaches, further reducing erroneous stream piracy. In situations where two vector stream features occupy the same grid cell, the new tool ensures that the larger stream, designated by higher TUCL, is given priority. TUCL‐based priority minimizes the impact of the topological errors that occur during the stream rasterization process on modeled regional drainage patterns. The test data demonstrated that TopologicalBreachBurn produces highly accurate and scale‐insensitive drainage patterns and watershed boundaries. The drainage divides of four large watersheds within the study region that were delineated from the TopologicalBreachBurn‐processed DEMs were found to be highly accurate when compared with the official watershed boundaries, even at the coarsest grid resolutions, with Kappa index of agreement values ranging from 0.952 to 0.921. The corresponding Kappa coefficient values for a traditional stream burning method (FillBurn) ranged from 0.953 to 0.490, demonstrating a significant decrease in mapping accuracy at coarser DEM grid resolutions. Copyright © 2015 John Wiley & Sons, Ltd.     

‘Out with the Old?’ Why coarse spatial datasets are still useful for catchment‐scale investigations of sediment (dis)connectivity

The increasing popularity of remote sensing techniques has created numerous options for researchers seeking spatial datasets, especially digital elevation models (DEMs), for geomorphic investigations. This yields an important question regarding what DEM resolution is most appropriate when answering questions of geomorphic significance. The highest possible resolution is not always the best choice for a particular research aim, and DEM resolution should be tailored to fit both the scale of investigation and the simplicity/complexity of modelling processes applied to the dataset. We find that DEM resolution has a significant effect on a simple model of bed load sediment connectivity in the Lockyer Valley, Queensland. We apply a simple bed load transport threshold to catchment DEMs at three different resolutions – 1 m, 5 m, and 25 m. We find that using a 1 m resolution DEM generates numerous disconnections along tributary channel networks that underestimates the sediment contributing area, i.e. effective catchment area (ECA), of seven tributary basins of Lockyer Creek. Utilizing a coarser (lower‐resolution) DEM helps eliminate erroneous disconnections, but can reduce the detail of stream network definition. We find that the 25 m resolution DEM provides the best measure of ECA for comparing sediment connectivity between tributary catchments. The utility of simple models and coarse‐resolution datasets is important for undertaking large, catchment‐scale geomorphic investigations. As catchment‐scale investigations are becoming increasingly entwined with river management and rehabilitation efforts, scientists need not embrace an ‘out with the old’ philosophy. Simple models and coarse‐resolution datasets can help better integrate geomorphic research with management strategies and provide inexpensive and quick first‐order insights into catchment‐scale processes that can help focus future management efforts. Copyright © 2017 John Wiley & Sons, Ltd.     

How does DEM resolution affect microtopographic characteristics,hydrologic connectivity,and modelling of hydrologic processes?

The resolution of a digital elevation model (DEM) is a crucial factor in watershed hydrologic and environmental modelling. DEM resolution can cause significant variability in the representation of surface topography, which further affects quantification of hydrologic connectivity and simulation of hydrologic processes. The objective of this study is to examine the effects of DEM resolution on (1) surface microtopographic characteristics, (2) hydrologic connectivity, and (3) the spatial and temporal variations of hydrologic processes. A puddle‐to‐puddle modelling system was utilized for surface delineation and modelling of the puddle‐to‐puddle overland flow dynamics, surface runoff, infiltration, and unsaturated flow for nine DEM resolution scenarios of a field plot surface. Comparisons of the nine modelling scenarios demonstrated that coarser DEM resolutions tended to eliminate topographic features, reduce surface depression storage, and strengthen hydrologic connectivity and surface runoff. We found that reduction in maximum depression storage and maximum ponding area was as high as 97.56% and 76.36%, respectively, as the DEM grid size increased from 2 to 80 cm. The paired t‐test and fractal analysis demonstrated the existence of a threshold DEM resolution (10 cm for the field plot), within which the DEM‐based hydrologic modelling was effective and acceptable. The effects of DEM resolution were further evaluated for a larger surface in the Prairie Pothole Region subjected to observed rainfall events. It was found that simulations based on coarser resolution DEMs (>10 m) tended to overestimate ponded areas and underestimate runoff discharge peaks. The simulated peak discharge from the Prairie Pothole Region surface reduced by approximately 50% as the DEM resolution changed from 2 to 90 m. Fractal analysis results elucidated scale dependency of hydrologic and topographic processes. In particular, scale analysis highlighted a unique constant–threshold–power relationship between DEM scale and topographic and hydrologic parameters/variables. Not only does this finding allow one to identify threshold DEM but also further develop functional relationships for scaling to achieve valid topographic characterization as well as effective and efficient hydrologic modelling. Copyright © 2016 John Wiley & Sons, Ltd.     

Snowpack variability across various spatio‐temporal resolutions

High‐resolution snow depth (SD) maps (1 × 1 m) obtained from terrestrial laser scanner measurements in a small catchment (0.55 km²) in the Pyrenees were used to assess small‐scale variability of the snowpack at the catchment and sub‐grid scales. The coefficients of variation are compared for various plot resolutions (5 × 5, 25 × 25, 49 × 49, and 99 × 99 m) and eight different days in two snow seasons (2011–2012 and 2012–2013). We also studied the relation between snow variability at the small scale and SD, topographic variables, small‐scale variability in topographic variables. The results showed that there was marked variability in SD, and it increased with increasing scales. Days of seasonal maximum snow accumulation showed the least small‐scale variability, but this increased sharply with the onset of melting. The coefficient of variation (CV) in snowpack depth showed statistically significant consistency amongst the various spatial resolutions studied, although it declined progressively with increasing difference between the grid sizes being compared. SD best explained the spatial distribution of sub‐grid variability. Topographic variables including slope, wind sheltering, sub‐grid variability in elevation, and potential incoming solar radiation were also significantly correlated with the CV of the snowpack, with the greatest correlation occurring at the 99 × 99 m resolution. At this resolution, stepwise multiple regression models explained more than 70% of the variance, whereas at the 25 × 25 m resolution they explained slightly more than 50%. The results highlight the importance of considering small‐scale variability of the SD for comprehensively representing the distribution of snowpack from available punctual information, and the potential for using SD and other predictors to design optimized surveys for acquiring distributed SD data. Copyright © 2014 John Wiley & Sons, Ltd.     

Evaluation of DEM generation based on Interferometric SAR using TanDEM-X data in Tokyo

This study is focused on the evaluation of a Digital Elevation Model (DEM) for Tokyo, Japan from data collected by the recently launched TerraSAR add-on for Digital Elevation Measurements (TanDEM-X), satellite of the German Aerospace Center (DLR). The aim of the TanDEM-X mission is to use Interferometric SAR techniques to generate a consistent high resolution global DEM dataset. In order to generate an accurate global DEM using TanDEM-X data, it is important to evaluate the accuracy at different sites around the world. Here, we report our efforts to generate a high-resolution DEM of the Tokyo metropolitan region using TanDEM-X data. We also compare the TanDEM-X DEM with other existing DEMs for the Tokyo region. Statistical techniques were used to calculate the elevation differences between the TanDEM-X DEM and the reference data. Two high-resolution LiDAR DEMs are used as independent reference data. The vertical accuracy of the TanDEM-X DEM evaluated using the Root Mean Square Error (RMSE) is considerably higher than the existing global digital elevation models. However, the local area DEM generated by Geospatial Information Authority of Japan (GSI DEM) showed the highest accuracy among all non-LiDAR DEM’s. The vertical accuracy in terms of RMSE estimated using the 2 m LiDAR as reference is 3.20 m for TanDEM-X, 2.44 m for the GSI, 7.00 m for SRTM DEM and 10.24 m for ASTER-GDEM. We also compared the accuracy of TanDEM-X with the other DEMs for different types of land cover classes. The results show that the absolute elevation error of TanDEM-X is higher for urban and vegetated areas, likewise to those observed for other global DEM’s. This is probably because the radar signals used by TanDEM-X tend to measure the first reflective surface that is encountered, which is often the top of the buildings or canopy. Hence, the TanDEM-X based DEM is more akin to a Digital Surface Model (DSM).     

Topographic accuracy assessment of bare earth lidar-derived unstructured meshes

This study is focused on the integration of bare earth lidar (Light Detection and Ranging) data into unstructured (triangular) finite element meshes and the implications on simulating storm surge inundation using a shallow water equations model. A methodology is developed to compute root mean square error (RMSE) and the 95th percentile of vertical elevation errors using four different interpolation methods (linear, inverse distance weighted, natural neighbor, and cell averaging) to resample bare earth lidar and lidar-derived digital elevation models (DEMs) onto unstructured meshes at different resolutions. The results are consolidated into a table of optimal interpolation methods that minimize the vertical elevation error of an unstructured mesh for a given mesh node density. The cell area averaging method performed most accurate when DEM grid cells within 0.25 times the ratio of local element size and DEM cell size were averaged. The methodology is applied to simulate inundation extent and maximum water levels in southern Mississippi due to Hurricane Katrina, which illustrates that local changes in topography such as adjusting element size and interpolation method drastically alter simulated storm surge locally and non-locally. The methods and results presented have utility and implications to any modeling application that uses bare earth lidar.     

Improvement of streams hydro‐geomorphological assessment using LiDAR DEMs

Hydro‐geomorphological assessments are an essential component for riverine management plans. They usually require costly and time‐consuming field surveys to characterize the spatial variability of key variables such as flow depth, width, discharge, water surface slope, grain size and unit stream power throughout the river corridor. The objective of this research is to develop automated tools for hydro‐geomorphological assessments using high‐resolution LiDAR digital elevation models (DEMs). More specifically, this paper aims at developing geographic information system (GIS) tools to extract channel slope, width and discharge from 1 m‐resolution LiDAR DEMs to estimate the spatial distribution of unit stream power in two contrasted watersheds in Quebec: a small agricultural stream (Des Fèves River) and a large gravel‐bed river (Matane River). For slope, the centreline extracted from the raw LiDAR DEM was resampled at a coarser resolution using the minimum elevation value. The channel width extraction algorithm progressively increased the centerline from the raw DEM until thresholds of elevation differences and slopes were reached. Based on the comparison with over 4000 differential global positioning system (GPS) measurements of the water surface collected in a 50 km reach of the Matane River, the longitudinal profile and slope estimates extracted from the raw and resampled LiDAR DEMs were in very good agreement with the field measurements (correlation coefficients ranging from 0 · 83 to 0 · 87) and can thus be used to compute stream power. The extracted width also corresponded very well to the channel as seen from ortho‐photos, although the presence of bars in the Matane River increased the level of error in width estimates. The estimated maximum unit stream power spatial patterns corresponded well with field evidence of bank erosion, indicating that LiDAR DEMs can be used with confidence for initial hydro‐geomorphological assessments. Copyright © 2013 John Wiley & Sons, Ltd.     

RIPGIS-NET: a GIS tool for riparian groundwater evapotranspiration in MODFLOW

RIPGIS-NET, an Environmental System Research Institute (ESRI's) ArcGIS 9.2/9.3 custom application, was developed to derive parameters and visualize results of spatially explicit riparian groundwater evapotranspiration (ETg), evapotranspiration from saturated zone, in groundwater flow models for ecohydrology, riparian ecosystem management, and stream restoration. Specifically RIPGIS-NET works with riparian evapotranspiration (RIP-ET), a modeling package that works with the MODFLOW groundwater flow model. RIP-ET improves ETg simulations by using a set of eco-physiologically based ETg curves for plant functional subgroups (PFSGs), and separates ground evaporation and plant transpiration processes from the water table. The RIPGIS-NET program was developed in Visual Basic 2005, .NET framework 2.0, and runs in ArcMap 9.2 and 9.3 applications. RIPGIS-NET, a pre- and post-processor for RIP-ET, incorporates spatial variability of riparian vegetation and land surface elevation into ETg estimation in MODFLOW groundwater models. RIPGIS-NET derives RIP-ET input parameters including PFSG evapotranspiration curve parameters, fractional coverage areas of each PFSG in a MODFLOW cell, and average surface elevation per riparian vegetation polygon using a digital elevation model. RIPGIS-NET also provides visualization tools for modelers to create head maps, depth to water table (DTWT) maps, and plot DTWT for a PFSG in a polygon in the Geographic Information System based on MODFLOW simulation results.     

Evaluation of remotely‐sensed DEMs and modification based on plausibility rules and initial sediment budgets of an artificially‐created catchment

To quantify landscape change resulting from processes of erosion and deposition and to establish spatially distributed sediment budgets, ‘models of change’ can be established from a time series of digital elevation models (DEMs). However, resolution effects and measurement errors in DEMs may propagate to these models. This study aimed to evaluate and to modify remotely‐sensed DEMs for an improved quantification of initial sediment mass changes in an artificially‐created catchment. DEMs were constructed from photogrammetry‐based, airborne (ALS) and ground‐based laser scanning (TLS) data. Regions of differing morphological characteristics and vegetation cover were delineated. Three‐dimensional (3D) models of volume change were established and mass change was derived from these models. DEMs were modified region‐by‐region for rill, interrill and alluvial areas, based on logical and hydro‐geomorphological principles. Additional DEMs were constructed by combining multi‐source, modified data. Models were evaluated by comparison with d‐GPS reference data and by considering sediment budget plausibility. Comprehensive evaluation showed that DEM usability depends on a relation between the technique used to obtain elevation data, surface morphology and vegetation cover characteristics. Photogrammetry‐based DEMs were suited to quantification of change in interrill areas but strongly underestimated surface lowering in erosion rills. TLS DEMs were best suited to rill areas, while ALS DEMs performed best in vegetation‐covered alluvial areas. Agreement with reference data and budget plausibility were improved by modifications to photogrammetry‐ and TLS‐based DEMs. Results suggest that artefacts in DEMs can be reduced and hydro‐geomorphic surface structures can be better represented by applying region‐specific modifications. Photogrammetry‐based DEMs can be improved by combining higher and lower resolution data in defined structural units and applying modifications based on principles given by characteristic hydro‐geomorphic evolution. Results of the critical comparative evaluation of remotely‐sensed elevation data can help to better interpret DEM‐based quantifications of earth‐surface processes. Copyright © 2012 John Wiley & Sons, Ltd.     

Evaluation of ASTER GDEM and SRTM and their suitability in hydraulic modelling of a glacial lake outburst flood in southeast Tibet

The resolution and accuracy of digital elevation models (DEMs) can affect the hydraulic simulation results for predicting the effects of glacial lake outburst floods (GLOFs). However, for the Tibetan Plateau, high‐quality DEM data are often not available, leaving researchers with near‐global, freely available DEMs, such as the Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (ASTER GDEM) and the Shuttle Radar Topography Mission data (SRTM) for hydraulic modelling. This study explores the suitability of these two freely available DEMs for hydraulic modelling of GLOFs. Our study focused on the flood plain of a potentially dangerous glacial lake in southeastern Tibet, to evaluate the elevation accuracy of ASTER GDEM and SRTM, and their suitability for hydraulic modelling of GLOFs. The elevation accuracies of ASTER GDEM and SRTM were first validated against field global position system (GPS) survey points, and then evaluated with reference to the relatively high precision of 1:50 000 scale DEM (DEM5) constructed from aerial photography. Moreover, the DEM5, ASTER GDEM and SRTM were used as basic topographic data to simulate peak discharge propagation, as well as flood inundation extent and depth in the Hydrologic Engineering Center's River Analysis System one‐dimensional hydraulic model. Results of the three DEM predictions were compared to evaluate the suitability of ASTER GDEM and SRTM for GLOF hydraulic modelling. Comparisons of ASTER GDEM and SRTM each with DEM5 in the flood plain area show root‐mean‐square errors between the former two as ± 15·4 m and between the latter two as ± 13·5 m. Although SRTM overestimates and ASTER GDEM underestimates valley floor elevations, both DEMs can be used to extract the elevations of required geometric data, i.e. stream centre lines, bank lines and cross sections, for flood modelling. However, small errors still exist in the cross sections that may influence the propagation of peak discharge. The flood inundation extent and mean water depths derived from ASTER GDEM predictions are only 2·2% larger and 2·3‐m deeper than that of the DEM5 predictions, whereas the SRTM yields a flood zone extent 6·8% larger than the DEM5 prediction and a mean water depth 2·4‐m shallower than the DEM5 prediction. The modelling shows that, in the absence of high‐precision DEM data, ASTER GDEM or SRTM DEM can be relied on for simulating extreme GLOFs in southeast Tibet. Copyright © 2011 John Wiley & Sons, Ltd.     

Effect of digital elevation model spatial resolution on depression storage

Surface water storage—including wetlands and other small waterbodies—has largely been disregarded in traditional hydrological models. In this paper, the grid resampling method is adopted to study the influence of the digital elevation model (DEM) grid resolution on depression storage (DS) considering different rainfall return periods. It is observed that the DEM grid size highly affects DS, and the higher the grid resolution is, the larger the DS value. However, when the grid resolution reaches a certain value, the maximum DS value decreases. This suggests that a critical grid resolution value exists at which the water storage capacity of depressions is maximized, namely, 20 m in this work (except for the overall area simulation under infiltration). This phenomenon is further verified in two test cases with and without the infiltration process, that is, calculations of the local area and without infiltration area, respectively. This research may facilitate the accurate computation of the DS process, which is greatly affected by the grid resolution, thereby improving the reliability of hydrological models.     

Application of globally available,coarse-resolution digital elevation models for delineating valley bottom segments of varying length across a catchment

The worldwide availability of digital elevation models (DEMs) has enabled rapid (semi-)automated mapping of earth surface landforms. In this paper, we first present an approach for delineating valley bottom extent across a large catchment using only publicly available, coarse-resolution DEM input. We assess the sensitivity of our results to variable DEM resolution and find that coarse-resolution datasets (90 m resolution) provide superior results. We also find that LiDAR-derived DEMs produce more realistic results than satellite-derived DEMs across the full range of topographic settings tested. Satellite-derived DEMs perform more effectively in moderate topographic settings, but fail to capture the subtleties of valley bottom extent in mild gradient, low-lying topography and in narrow headwater reaches. Second, we present a semi-automated technique within ArcGIS for delineating valley bottom segments using DEM-derived network scale metrics of valley bottom width and slope. We use an unsupervised machine-learning technique based on the k-means clustering algorithm to solve a conundrum in GIS-based geomorphic analysis of rivers: the delineation of valley bottom segments of variable length. The delineation of valley bottom segments provides a coarse-scale entry point into automated geomorphic analysis and characterization of river systems. © 2020 John Wiley & Sons, Ltd.     

Assessment of terrestrial laser scanning technology for obtaining high‐resolution DEMs of soils

Terrestrial Laser Scanners (TLS) provide a non‐contact method to measure soil microtopography of relatively large surface areas. The appropriateness of the technology in relatation to the derived Digital Elevation Models (DEM) however has not been reported. The suitability of TLS for soil microtopography measurements was tested on‐field for three large soil surface areas in agricultural fields. The acquired point clouds were filtered with a custom cloud import algorithm, and converted into digital elevation models (DEM) of different resolutions. To assess DEM quality, point clouds measured from different viewpoints were statistically compared. The statistical fit between point clouds from different viewpoints depends on spatial resolution of the DEM. The best results were obtained at the higher resolutions (0.02 to 0.04 cm), where less than 5 % of the grid cells showed significant differences between one viewpoint and the next (p < 0.01). Copyright © 2012 John Wiley & Sons, Ltd.     

BOOK REVIEWS

Abstract

A distributed eco-hydrological model based on soil—vegetation—atmosphere transfer processes is applied to estimate actual evapotranspiration (ET) and gross primary production (GPP) over the Wuding River basin, Loess Plateau, China, based on digital elevation model, vegetation and soil information between 2000 and 2003 over three grid sizes: 250 m, 1 km and 8 km. The spatial patterns of annual ET and GPP are related to precipitation variability and land-use/cover conditions. The grid size is shown to affect the spatial patterns of annual ET and GPP, the effect on GPP being more significant than that on ET. Geostatistical and regression analyses demonstrate that precipitation and vegetation influence the scaling effect of ET and GPP in a complex way. When precipitation is high, the scaling effect of ET is more dependent on precipitation. The scaling effect of ET and GPP from 1-km to 8-km grid size is much larger than that from 250-m to 1-km grid size, showing the 1-km grid size to be a feasible choice for simulation of their spatial patterns. Although the annual GPP is more sensitive to the grid size than annual ET, both daily ET and daily GPP averaged over the whole basin seem to be insensitive to the grid size, illustrating that the coarse grid size can be used to simulate spatially-averaged variables without losing much accuracy.     

Regional assimilation of in situ observed soil moisture into the VIC model considering spatial variability

ABSTRACT

In order to improve the soil moisture (SM) modelling capacity, a regional SM assimilation scheme based on an empirical approach considering spatial variability was constructed to assimilate in situ observed SM data into a hydrological model. The daily variable infiltration capacity (VIC) model was built to simulate SM in the Upper Huai River Basin, China, with a resolution of 5 km × 5 km. Through synthetic assimilation experiments and validations, the assimilated SM was evaluated, and the assimilation feedback on evapotranspiration (ET) and streamflow are analysed and discussed. The results show that the assimilation scheme improved the SM modelling capacity, both spatially and temporally. Moreover, the simulated ET was continually affected by changes in SM simulation, and the streamflow predictions were improved after applying the SM assimilation scheme. This study demonstrates the potential value of in situ observations in SM assimilation, and provides valuable ways for improving hydrological simulations.     

Field Test of a Hybrid Finite‐Difference and Analytic Element Regional Model

Regional finite‐difference models often have cell sizes that are too large to sufficiently model well‐stream interactions. Here, a steady‐state hybrid model is applied whereby the upper layer or layers of a coarse MODFLOW model are replaced by the analytic element model GFLOW, which represents surface waters and wells as line and point sinks. The two models are coupled by transferring cell‐by‐cell leakage obtained from the original MODFLOW model to the bottom of the GFLOW model. A real‐world test of the hybrid model approach is applied on a subdomain of an existing model of the Lake Michigan Basin. The original (coarse) MODFLOW model consists of six layers, the top four of which are aggregated into GFLOW as a single layer, while the bottom two layers remain part of MODFLOW in the hybrid model. The hybrid model and a refined “benchmark” MODFLOW model simulate similar baseflows. The hybrid and benchmark models also simulate similar baseflow reductions due to nearby pumping when the well is located within the layers represented by GFLOW. However, the benchmark model requires refinement of the model grid in the local area of interest, while the hybrid approach uses a gridless top layer and is thus unaffected by grid discretization errors. The hybrid approach is well suited to facilitate cost‐effective retrofitting of existing coarse grid MODFLOW models commonly used for regional studies because it leverages the strengths of both finite‐difference and analytic element methods for predictions in mildly heterogeneous systems that can be simulated with steady‐state conditions.     

Up-scaling of SEBAL derived evapotranspiration maps from Landsat (30 m) to MODIS (250 m) scale

Remotely sensed imagery of the Earth’s surface via satellite sensors provides information to estimate the spatial distribution of evapotranspiration (ET). The spatial resolution of ET predictions depends on the sensor type and varies from the 30–60 m Landsat scale to the 250–1000 m MODIS scale. Therefore, for an accurate characterization of the regional distribution of ET, scaling transfer between images of different resolutions is important. Scaling transfer includes both up-scaling (aggregation) and down-scaling (disaggregation). In this paper, we address the up-scaling problem.The Surface Energy Balance Algorithm for Land (SEBAL) was used to derive ET maps from Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and Moderate Resolution Imaging Spectroradiometer (MODIS) images. Landsat 7 bands have spatial resolutions of 30–60 m, while MODIS bands have resolutions of 250, 500 and 1000 m. Evaluations were conducted for both “output” and “input” up-scaling procedures, with aggregation accomplished by both simple averaging and nearest neighboring resampling techniques. Output up-scaling consisted of first applying SEBAL and then aggregating the output variable (daily ET). Input up-scaling consisted of aggregating 30 m Landsat pixels of the input variable (radiance) to obtain pixels at 60, 120, 250, 500 and 1000 m before SEBAL was applied. The objectives of this study were first to test the consistency of SEBAL algorithm for Landsat and MODIS satellite images and second to investigate the effect of the four different up-scaling processes on the spatial distribution of ET.We conclude that good agreement exists between SEBAL estimated ET maps directly derived from Landsat 7 and MODIS images. Among the four up-scaling methods the output simple averaging method produced aggregated data and aggregated differences with the most statistically and spatially predictable behavior. The input nearest neighbor method was the least predictable but was still acceptable. Overall, the daily ET maps over the Middle Rio Grande Basin aggregated from Landsat images were in good agreement with ET maps directly derived from MODIS images.