Simulated Hydrological Fluxes Research Articles

Reliability of satellite-derived precipitation data in driving hydrological simulations: A case study of the upper Huaihe River basin, China

• SPD are better at capturing temporal rather than spatial variations in precipitation. • SPD-driven models are typically better at characterizing temporal variations in HFS. • SPD-driven models exhibited large uncertainty in reproducing daily HFS. • Effective reproduction of HFS has more stringent requirements on the quality of SPD. • Model calibration based on streamflow may hinder the best reproduction of HFS. The vigorous development of satellite precipitation observations has gained widespread attention in the field of hydrology. Many studies have explored the reliability of hydrological models driven by satellite precipitation data (SPD) to reproduce streamflow. However, the reliability of SPD in the simulation of other hydrological processes remains unclear, even though a full understanding of the dynamic variations in hydrological processes is essential for the scientific management of water resources. In this study, we investigated the effect of SPD uncertainty on the distributed hydrological model in reproducing hydrological simulations. The investigation was conducted in the upper Huaihe River basin, which has a high-density ground precipitation observation network. The uncertainty inherent in 8 types of SPD in characterizing the temporal and spatial variations in precipitation was comprehensively examined. The Variable Infiltration Capacity hydrological model (VIC) was then applied to further explore the reliability of the simulated hydrological fluxes and states (HFS) driven by the selected SPD over multiple temporal-spatial scales. The results showed that: (1) the selected SPD tend to have greater uncertainty in recognizing spatial variations in precipitation than in identifying temporal variations; the VIC models driven by the selected SPD generally performed better in characterizing temporal variations in HFS than in reproducing their spatial variations. In addition, the corrected SPD (CSPD) are more suitable for HFS simulations than the uncorrected SPD (USPD); (2) the effective reproduction of the spatio-temporal variations in HFS has more stringent requirements on the quality of SPD than the satisfactory reproduction of streamflow. For the gridded scale simulations, the selected SPD-driven models exhibited large uncertainties in reproducing spatio-temporal variations in daily HFS. In contrast, although these models significantly improved the simulation performance of monthly HFS, they were still relatively deficient in reproducing their spatial variations. In terms of the basin-scale simulations, the CSPD-driven models tend to reliably reproduce monthly HFS; and (3) independent calibration can allow the selected SPD-driven models to reproduce streamflow more effectively, but it may not result in the best reproduction of HFS. This study provides guidance for strengthening the application of SPD in hydrological modeling and provides feedback for further improving the quality of SPD.

On the Uncertainty Induced by Pedotransfer Functions in Terrestrial Biosphere Modeling

AbstractHydrological, ecohydrological, and terrestrial biosphere models depend on pedotransfer functions for computing soil hydraulic parameters based on easily measurable variables, such as soil textural and physical properties. Several pedotransfer functions have been derived in the last few decades, providing divergent estimates of soil hydraulic parameters. In this study, we quantify how uncertainties embedded in using different pedotransfer functions propagate to ecosystem dynamics, including simulated hydrological fluxes and vegetation response to water availability. Using a state‐of‐the‐art ecohydrological model applied at 79 sites worldwide, we show that uncertainties related to pedotransfer functions can affect both hydrological and vegetation dynamics. Uncertainties in evapotranspiration, plant productivity, and vegetation structure, quantified as leaf area, are in the order of ∼10% at annual time scales. Runoff and groundwater recharge uncertainties are one order of magnitude larger. All uncertainties are largely amplified when small‐scale topography is taken into account in a distributed domain, especially for water‐limited ecosystems with low permeability soils. Overall, pedotransfer function related uncertainties for a given soil type are higher than uncertainties across soil types in both hydrological and ecosystem dynamics. The magnitude of uncertainties is climate‐dependent but not soil type‐dependent. Evapotranspiration, vegetation structure, and plant productivity uncertainties are higher in water‐limited semiarid climates, whereas groundwater recharge uncertainties are higher in climates where potential evapotranspiration is comparable to precipitation.

Using observed soil moisture to constrain the uncertainty of simulated hydrological fluxes

AbstractUsing data from five long‐term field sites measuring soil moisture, we show the limitations of using soil moisture observations alone to constrain modelled hydrological fluxes. We test a land surface model, Modélisation Environnementale communautaire‐Surface Hydrology/Canadian Land Surface Scheme, with two configurations: one where the soil hydraulic properties are determined using a pedotransfer function (the texture‐based calibration) and one where they are assigned directly (the hydraulic properties‐based calibration). The hydraulic properties‐based calibration outperforms the texture‐based calibration in terms of reproducing changes in soil moisture storage within a 1.6 m deep profile at each site, but both perform reasonably well, especially in the summer months. When the models are constrained using observations of changes in soil moisture, the predicted hydrological fluxes are subject to very large uncertainties associated with equifinality. The uncertainty is larger for the hydraulic properties‐based calibration, even though the performance was better. We argue that since the pedotransfer functions constrain the model parameters in the texture‐based calibrations in an unrealistic way, the texture‐based calibration underestimates the uncertainty in the fluxes. We recommend that reproducing observed cumulative changes in soil moisture storage should be considered a necessary but insufficient criterion of model success. Additional sources of information are needed to reduce uncertainties, and these could include improved estimation of the soil hydraulic properties and direct observations of fluxes, particularly evapotranspiration.

Assessment of climate change and its impact on hydrological regimes and biomass yield of a tropical river basin

Assessing climate change impact on hydrology and biomass yield of a tropical river basin is necessary for formulating a suitable coping strategy. A hydrological modelling framework was established for Subarnarekha river basin through calibration and validation of SWAT model with the observed river discharge at four gauging locations. The global sensitivity analysis was performed to establish the robustness and stability of the model to reproduce outputs resultant to various extremes of precipitation and other weather events. The 5-GCMs, namely HadGEM2-ES, MIROC-ESM, NCAR-CCSM4, CSIRO-MK3.6, and CESM1-CAM5 were analyzed and HadGEM2-ES was selected based on its performance with respect to ensemble of remaining 4 GCMs (p ≤ 0.05). The AR5-HadGEM2-ES monthly database (1 km2 resolutions) was used to generate bias factor for preparing daily climatic variables in the future projection which was employed as a forcing to simulate river discharge and other hydrological fluxes for the future climate scenario. Increase in precipitation from 14 to 36%, the runoff increased from 39.7 to 104.1%. When compared to the present period, an increase in monsoon runoff is expected 100 and 200% during 2030 and 2080, respectively. Higher degree of uncertainty in expected runoff volumes was expected in mid- and far future time period. Intra-RCP scenarios analyses indicated a significant surge in monsoon season runoff volume during 2070 and 2080 and insignificant surge during 2030 and 2050. As the basin constitute a rice ecosystem, the simulation approach involved a detailed accounting of the operational activities of a rice to realistically capture its manifestation in the annual accrual of actual evapotranspiration in the simulated hydrological fluxes. During monsoon season, potential evapotranspiration (PET) and actual evapotranspiration (AET) increased by 2.2–12.7% and 1.0–9.0%, respectively. Following simulation output, it was found that the basin was expected to suffer a crop biomass loss of 2 to 3% due to climate change. Simple yield response technique to estimate biomass yield losses was found to be promising alternatives to complex crop modeling studies.

On Approaches to Analyze the Sensitivity of Simulated Hydrologic Fluxes to Model Parameters in the Community Land Model

Effective sensitivity analysis approaches are needed to identify important parameters or factors and their uncertainties in complex Earth system models composed of multi-phase multi-component phenomena and multiple biogeophysical-biogeochemical processes. In this study, the impacts of 10 hydrologic parameters in the Community Land Model on simulations of runoff and latent heat flux are evaluated using data from a watershed. Different metrics, including residual statistics, the Nash–Sutcliffe coefficient, and log mean square error, are used as alternative measures of the deviations between the simulated and field observed values. Four sensitivity analysis (SA) approaches, including analysis of variance based on the generalized linear model, generalized cross validation based on the multivariate adaptive regression splines model, standardized regression coefficients based on a linear regression model, and analysis of variance based on support vector machine, are investigated. Results suggest that these approaches show consistent measurement of the impacts of major hydrologic parameters on response variables, but with differences in the relative contributions, particularly for the secondary parameters. The convergence behaviors of the SA with respect to the number of sampling points are also examined with different combinations of input parameter sets and output response variables and their alternative metrics. This study helps identify the optimal SA approach, provides guidance for the calibration of the Community Land Model parameters to improve the model simulations of land surface fluxes, and approximates the magnitudes to be adjusted in the parameter values during parametric model optimization.

Satellite precipitation in southeastern South America: how do sampling errors impact high flow simulations?

Satellite precipitation estimates are increasingly available at temporal and spatial scales of interest to hydrological applications and with the potential for improving flood forecasts in data-sparse regions. This study evaluates the effect of sampling error on simulated large flood events. Synthetic precipitation fields were generated in Monte Carlo fashion by perturbing observed precipitation fields with sampling errors based on 1, 2 and 6 h intervals. The variable infiltration capacity hydrological model was used to assess the impact of these errors on simulated high flow events in the Iguazu basin, a rain-dominated, subtropical basin in southeastern South America. Results showed that unbiased errors in daily error-corrupted precipitation fields introduced bias in the simulated hydrologic fluxes and states. The overall bias for error-corrupted daily streamflows was positive and its magnitude increased with larger sampling intervals. However, for high flow events, the bias was negative as a result of an increase in simulated infiltration and changes in precipitation variability. Errors in precipitation also affected the magnitude and volume of the peak events but did not change the first two statistical moments of the peaks indicating that non-linearities in the hydrological system preserve the statistical properties of high flows in the basin. Caution is needed when using satellite products for hydrological applications that require the estimation of large peaks and volumes.

Biohydrologic effects of eastern redcedar encroachment into grassland, Oklahoma, USA

Woody encroachment affects the biohydrology of rangelands worldwide and can increase evapotranspiration by increasing plant rooting depth, increasing the duration of the growing season, or by initiating a process of hydrologic recovery in formerly overgrazed landscapes. Eastern redcedar (Juniperus virginiana) is encroaching rapidly into rangelands in the Southern Great Plains of the USA, and beyond, including Oklahoma. However, the degree to which increasing growing season duration causes higher evapotranspiration after encroachment is not known. Here we show that increasing the duration of the growing season in north-central Oklahoma’s water-limited climate from seven months (April–October) to 12 months increases modeled evapotranspiration only marginally, from 95% to 97% of precipitation. However, this increase in evapotranspiration with woody encroachment into grassland corresponded to a two-thirds reduction in deep drainage. This study’s estimate of the hydrologic effects of eastern redcedar encroachment is likely to be highly conservative because it does not take into account the runoff-inducing effects of livestock grazing. Comparing simulated hydrologic fluxes in the present study to past work measuring runoff from grazinglands suggests that eastern redcedar encroachment into overgrazed rangelands is likely to increase evapotranspiration significantly. Whether or not eastern redcedar encroachment effects on evapotranspiration are discernable at the watershed scale will depend on the extent of encroachment throughout the watershed. Further research is necessary to quantify how the hydrologic effects of eastern redcedar encroachment vary due to climatic gradient.

Monte Carlo assessment of uncertainty in the simulated hydrological response to land use change

We quantified the uncertainty in hydrological response for a set of land use change scenarios by varying plant parameters within realistic uncertainty bounds in a Monte Carlo analysis. The results show that simulated hydrological fluxes significantly change after the introduction of outwintering suckler cow management, despite the presence of a significant amount of output uncertainty due to uncertainty in the plant parameterisation. The key to a proper uncertainty assessment was to consider the uncertainty in the difference between the scenarios instead of the absolute uncertainty of each single scenario. Additionally, a sensitivity analysis showed that changing soil properties in response to land use change does not result in significantly different results in the scenario analysis.

The effect of afforestation on water recharge and nitrogen leaching in The Netherlands

Water balances and nitrogen budgets were studied in two chronosequences of oak and spruce on former arable land. Quantity and quality of rainfall and throughfall, soil water contents and concentrations in the soil solution were measured during a period of 1–2 years. Hydrological fluxes were calculated using the soil hydrological model SWAP. Nitrogen leaching fluxes were based on monthly measured concentrations and simulated hydrological fluxes. Results showed that water recharge declined from approximately 485 mm/yr in arable land to 172 mm in the 18-year old oak stand and approximately 100 mm in the 13 and 14-year old spruce stands. For both chronosequences the decline in water recharge upon afforestation can be described by a power function; the exponent being −0.22 for oak and somewhat higher, −0.31, for spruce. Nitrogen leaching fluxes were negligible in the spruce stands and declined with age in the oak stands, from 16 kg/ha/yr at the youngest stand to 8 kg/ha/yr at the 18-year old stand. The nitrogen budget for the four oak stands increased with age. An explanation for this unexpected result may be the declining release of nitrogen by mineralization of organic matter present in the (former) agricultural soil. The data provide valuable information for the validation of simulation models and decision support systems used for policy decisions.

Effect of precipitation sampling error on simulated hydrological fluxes and states: Anticipating the Global Precipitation Measurement satellites

Precipitation is the single most important determinant of the fluxes and states of the land surface hydrological system and the most important atmospheric input to hydrological models. Satellite‐based precipitation estimates, such as those anticipated from the Global Precipitation Measurement (GPM) satellites, hold great promise for application in hydrologic simulation and prediction, especially in parts of the world where surface observation networks are sparse. However, the usefulness of these precipitation products for hydrological applications will depend on their error characteristics. Of particular interest in satellite‐derived precipitation estimates is the sampling error, that is, the error in accumulated precipitation due to periodic sampling of the precipitation rate. To assess the effect of this error on simulated hydrological fluxes and states, synthetic error fields were imposed on an observation‐based 1/2° latitude/longitude gridded precipitation data set. In turn, the generated precipitation fields were used as input to a macroscale hydrology model (MHM). Our results show that (1) streamflow errors were large for small drainage areas but decreased rapidly for drainage areas larger than about 50,000 km2. Much of the streamflow error is associated with fast (near‐surface) runoff response. (2) Streamflow estimates were biased upward due to sampling errors, with the bias increasing with sampling interval and with drainage area. Evapotranspiration was biased downward in a compensating amount. (3) Spatial correlation of precipitation errors reduced the rate at which errors decreased with drainage area for all variables investigated, but the differences between the correlated and uncorrelated error cases were smaller for streamflow and evapotranspiration than for precipitation.

Sensitivity of simulated hydrological fluxes towards changes in soil properties in response to land use change

Current model studies on the impact of land use change on water resources often simulate changes in land use without considering changes in the soil properties due to the change in land use. In this study, an artificial study catchment representing the Dill catchment (Germany) was used within the eco-hydrological model SWAT-G to study the sensitivity of SWAT-G simulations towards changes in soil properties during land use change. Since there is little information on these soil–vegetation interactions, we performed a model sensitivity study to investigate the impact of changes in the depth of the top soil layer, bulk density, saturated hydraulic conductivity and available water content on several simulated hydrological fluxes. To assess the significance of the simulated changes due to the changing soil properties, we compared the model sensitivity with the uncertainty in the hydrological fluxes due to the uncertainty in the parameterization of the plant parameters. The results showed that the changes in soil properties due to a land use transition from cropland to pasture only have a minor impact on the simulated mean annual, summer and winter runoff and actual evapotranspiration. Soil–vegetation interactions have a stronger impact on the simulated mean surface runoff, although the absolute contribution of this flux is small in our conceptualization of the Dill catchment. A comparison of the sensitivity and uncertainty of the simulated hydrological fluxes led to the conclusion that changes in soil properties due to land use change are relatively unimportant in our model of the Dill catchment in the light of the low sensitivity of the dominating hydrological fluxes and the large output uncertainty due to the plant parameter uncertainty.

Improving the precision of simulated hydrologic fluxes in land surface models

The numerical method for estimating soil moisture transport coefficients in land surface models (LSMs) is evaluated through comparison to a weighted‐average method based on successive steady states [Warrick, 1991] and a proposed new scheme [Dong and Wang, 1997]. The focus is on situations with large gradients of soil moisture. The reference cases used to evaluate the performance of the various methods are based on numerical integrations with fine spatial resolution and small time steps. A series of tests were performed to detect sources of discrepancies and to assess the impact of various numerical methods on the simulation of evaporation, transpiration, and drainage. Off‐line LSM simulations driven by observed atmospheric forcings were analyzed to understand the propagation of errors between the various hydrologic processes. We suggest a simple modification to LSM that can improve the precision of simulated hydrologic fluxes without increasing vertical resolution.