Comparison of Evapotranspiration Simulation Performance by APEX Model in Dryland and Irrigated Cropping Systems

Accurate estimation of evapotranspiration (ET) is essential to improve water use efficiency of crop production systems managed under different water regimes. The Agricultural Policy/Environmental eXtender (APEX) model was used to simulate ET using four potential ET (ET_p) methods. The objectives were to determine sensitive ET parameters in dryland and irrigated cropping systems and compare ET simulation in the two systems using multiple performance criteria. Measured ET and crop yield data from lysimeter fields located in the United States Department of Agriculture‐Agricultural Research Service Bushland, Texas were used for evaluation. The number of sensitive parameters was higher for dryland (11–14) than irrigated cropping systems (6–8). Only four input parameters: soil evaporation plant cover factor, root growth soil strength, maximum rain intercept, and rain intercept coefficient were sensitive in both cropping systems. Overall, it is possible to find a set of robust parameter values to simulate ET accurately in APEX in both cropping systems using any ET_p method. However, more computation time is required for dryland than irrigated cropping system due to a relatively larger number of sensitive input parameters. When all inputs are available, the Penman–Monteith method takes the shortest computation time to obtain one model run with robust parameter values in both cropping systems. However, in areas with limited datasets, one can still obtain reasonable ET simulations using either Priestley–Taylor or Hargreaves. Editor's note : This paper is part of the featured series on Optimizing Ogallala Aquifer Water Use to Sustain Food Systems. See the February 2019 issue for the introduction and background to the series.     

ADEQUACY OF SELECTED EVAPOTRANSPIRATION APPROXIMATIONS FOR HYDROLOGIC SIMULATION1

ABSTRACT: Evapotranspiration (ET) approximations, usually based on computed potential ET (PET) and diverse PET‐to‐ET conceptualizations, are routinely used in hydrologic analyses. This study presents an approach to incorporate measured (actual) ET data, increasingly available using micrometeorological methods, to define the adequacy of ET approximations for hydrologic simulation. The approach is demonstrated at a site where eddy correlation‐measured ET values were available. A baseline hydrologic model incorporating measured ET values was used to evaluate the sensitivity of simulated water levels, subsurface recharge, and surface runoff to error in four ET approximations. An annually invariant pattern of mean monthly vegetation coefficients was shown to be most effective, despite the substantial year‐to‐year variation in measured vegetation coefficients. The temporal variability of available water (precipitation minus ET) at the humid, subtropical site was largely controlled by the relatively high temporal variability of precipitation, benefiting the effectiveness of coarse ET approximations, a result that is likely to prevail at other humid sites.     

Using Landsat data to estimate evapotranspiration of winter wheat

An evapotranspiration (ET) model that accurately estimates daily water use and soil moisture on a regional basis is required for many agricultural and hydrological studies. The model should use meterological data that are readily available and crop information that is responsive to the changing vigor of the plants.We evaluated an ET model with a weighing lysimeter and then applied it to winter wheatfields at four Kansas locations. Model inputs are solar radiation, temperature, precipitation, and leaf area index (LAI); included in the outputs are estimates of transpiration, evaporation, and soil moisture. An equation was developed to estimate LAI from Landsat data. Because LAI can be estimated from satellites, the ET model can potentially be used on a regional basis.     

Riparian Ecosystem Management Model: Sensitivity to Soil,Vegetation, and Weather Input Parameters1

Abstract: The Riparian Ecosystem Management Model (REMM) was developed by the U.S. Department of Agriculture‐Agriculture Research Service (USDA‐ARS) and its cooperators to design and evaluate the efficiency of riparian buffer ecosystems for nonpoint source pollution reduction. REMM requires numerous inputs to simulate water movement, sediment transport, and nutrient cycling in the buffer system. In order to identify critical model inputs and their uncertainties, a univariate sensitivity analysis was conducted for nine REMM output variables. The magnitude of each input parameter was changed from ?50% to +50% from the baseline data in 12 intervals or, in some cases, the complete range of an input was tested. Baseline model inputs for the sensitivity analysis were taken from Gibbs Farm, Georgia, where REMM was tested using a 5‐year field dataset. Results of the sensitivity analysis indicate that REMM responses were most sensitive to weather inputs, with minimum daily temperature having the greatest impact on the nitrogen‐related outputs. For example, the 100% change (?50% to +50%) in minimum daily temperature input values yielded a 164.4% change in total nitrogen (N), a 109.3% change in total nitrate (NO₃), and a 127.1% change in denitrification. REMM was most sensitive to precipitation with regard to total flow leaving the riparian vegetative buffer zone (199.8%) and sediment yield (138.2%). Deep seepage (12.2%), volumetric water content (24.8%), and pore size index (6.5%) in the buffer soil profile were the most influential inputs for the output water movement. Sediment yield was most sensitive to Manning’s coefficient (46.6%), bare soil percent (40.7%), and soil permeability (6.1%). For vegetation, specific leaf area, growing degree day coefficients, and maximum root depth influenced the nitrogen related outputs. Overall results suggest that because of the high sensitivity to weather parameters, on‐site weather data is needed for model calibration and validation. The model’s relatively low sensitivity to vegetation parameters also appears to support the use of regional vegetation datasets that would simplify model implementation without compromising results.     

Assessing Calibration Uncertainty and Automation for Estimating Evapotranspiration from Agricultural Areas Using METRIC

Agricultural irrigation accounts for a large fraction of the total water use in the western United States. The Mapping Evapotranspiration at high Resolution with Internalized Calibration (METRIC) remote sensing energy balance model is being used to estimate historical agricultural water use in western Nevada to evaluate basin‐wide water budgets. Each METRIC evapotranspiration (ET) estimate must be calibrated by a trained user, which requires some iterative time investment and results in variation in ET estimates between users. An automated calibration algorithm for the METRIC model was designed to generate ET estimates comparable to those from trained users by mimicking the manual calibration process. Automated calibration allows for rapid generation of METRIC ET estimates with minimal manual intervention, as well as uncertainty and sensitivity analysis of the model. The variation in ET estimates generated by the automated calibration algorithm was found to be similar to the variation in manual ET estimates. Results indicate that uncertainty was highest for fields with low ET levels and lowest for fields with high ET levels, with a seasonal mean uncertainty of approximately 5% for all fields. In addition, in a blind comparison, automated daily and seasonal ET estimates compared well with flux tower measurement ET data at multiple sites. Automated methods can generate first‐order ET estimates that are similar to time intensive manual efforts with less time investment.     

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

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

Analyzing the Variability of Remote Sensing and Hydrologic Model Evapotranspiration Products in a Watershed in Michigan

The goal of this paper was to statistically explore the spatiotemporal performance of remotely sensed actual evapotranspiration (ETa) datasets and a remotely sensed ensemble in a region that lacks observed data. The remotely sensed datasets were further compared with ETa results from a physically based hydrologic model (Soil and Water Assessment Tool) to examine the differences and determine the level of agreement between the ETa datasets and the model outputs. ETa datasets were compared on temporal (i.e., monthly and seasonal basis) and spatial (i.e., landuse) scales at both watershed and subbasin levels. The results showed a lack of consistent similarities and differences among the datasets when evaluating the monthly ETa variations; however, the seasonal aggregated data presented more consistent similarities and differences during the spring and summer compared to the fall and winter. Meanwhile, spatial analysis of the datasets showed the MOD16A2 500 m ETa product was the most versatile of the tested datasets, being able to differentiate between landuses during all seasons. Furthermore, the use of an averaging ensemble was able to improve overall ETa performance in the study area. This study showed that the remotely sensed ETa products are not similar throughout the year, but the appropriate application periods for different ETa products were identified. Finally, spatial variabilities of the ETa products are more in tune with landuse and climate characteristics.     

Development of the Spatial Rainfall Generator (SRGEN) for the Agricultural Policy/Environmental Extender Model

Accurate spatial representation of climatic patterns is often a challenge in modeling biophysical processes at the watershed scale, especially where the representation of a spatial gradient in rainfall is not sufficiently captured by the number of weather stations. The spatial rainfall generator (SRGEN) is developed as an extension of the “weather generator” (WXGEN), a component of the Agricultural Policy/Environmental eXtender (APEX) model. SRGEN generates spatially distributed daily rainfall using monthly weather statistics available at multiple locations in a watershed. The spatial rainfall generator as incorporated in APEX is tested on the Cowhouse watershed (1,178 km²) in central Texas. The watershed presented a significant spatial rainfall gradient of 2.9 mm/km in the lateral (north‐south) directions based on four rainfall gages. A comparative analysis between SRGEN and WXGEN indicates that SRGEN performs well (PBIAS = 2.40%). Good results were obtained from APEX for streamflow (NSE = 0.99, PBIAS = 8.34%) and NO₃‐N and soluble P loads (PBIAS ≈ 6.00% for each, respectively). However, APEX underpredicted sediment yield and organic N and P loads (PBIAS: 24.75‐27.90%) with SRGEN, although its uncertainty in output was lower than WXGEN results (PBIAS: ?13.02 to ?46.13%). The overall improvement achieved in rainfall generation by SRGEN is demonstrated to be effective in the improving model performance on flow and water quality output.     

Predicting soil erosion for alternative land uses

The APEX (Agricultural Policy-Environmental eXtender) model developed in the United States was calibrated for northwestern China's conditions. The model was then used to investigate soil erosion effects associated with alternative land uses at the ZFG (Zi-Fang-Gully) watershed in northwestern China. The results indicated that the APEX model could be calibrated reasonably well (+/-15% errors) to fit those areas with >50% slope within the watershed. Factors being considered during calibration include runoff, RUSLE (Revised Universal Soil Loss Equation) slope length and steepness factor, channel capacity flow rate, floodplain saturated hydraulic conductivity, and RUSLE C factor coefficient. No changes were made in the APEX computer code. Predictions suggest that reforestation is the best practice among the eight alternative land uses (the status quo, all grass, all grain, all grazing, all forest, half tree and half grass, 70% tree and 30% grain, and construction of a reservoir) for control of water runoff and soil erosion. Construction of a reservoir is the most effective strategy for controlling sediment yield although it does nothing to control upland erosion. For every 1 Mg of crop yield, 11 Mg of soil were lost during the 30-yr simulation period, suggesting that expanding land use for food production should not be encouraged on the ZFG watershed. Grass species are less effective than trees in controlling runoff and erosion on steep slopes because trees generally have deeper and more stable root systems.     

UPLAND SOIL EROSION SIMULATION FOR AGRICULTURAL WATERSHEDS1

ABSTRACT: A soil erosion simulation model that considered the physical conditions of agricultural watersheds and that interfaced with the modified USDAHL-74 watershed hydrology model was developed. The erosion model simulates the detachment and transport of soil particles caused by raindrop impact and overland flow from rill and interrill areas. The model considers temporal and spatial variation of plant residue, crop canopy cover, snow cover, and the moisture content of surface soil as modifying factors of the erosive forces of raindrop impact and overland flow. The hydrology model simulates overland flow and some of the physical parameters that are used in the erosion model. The simulation is executed in the time interval determined by the rainfall rate or snowmelt rate. The erosion model compares the transport capacity of the overland flow and the sediment loaded in the overland flow to determine the fate account for the free soil particles that have already been detached and are readily available to be transported by the overland flow. The model was tested with data from two small agricultural watersheds in the Palouse region of the Pacific Northwest dryland. The model was calibrated by trial-and-error to determine the coefficients of the model.     

APPLICATION OF THE GREEN-AMPT INFILTRATION EQUATION TO WATERSHED MODELING1

ABSTRACT: A computer model was developed, based on the Green-Ampt infiltration equation, to computed rainfall excess for a single precipitation event. The model requires an estimate of parameters related to hydraulic conductivity, wetting front section, and fillable porosity of the soil layers. Values of parameters were estimated from soil textural averages or regression equations based on percent sand, percent clay, and porosity. Average values of effective porosity and wetting front suction were largely acceptable due to the relatively low variability and low model sensitivity to the parameters. Hydraulic conductivity was the most erratic constituent of the loss rate computation due to the high variability and the high sensitivity of the computed infiltration to the parameter. The performance of the Green-Ampt infiltration model was tested through a comparison with the SCS curve number procedure. Seven watersheds and 23 storms with precipitation of one inch or greater were used in the comparison. For storms with less than one inch of rainfall excess, the SCS curve number procedure generally gave the best results; however, for six of the seven storms with precipitation excess greater than one inch, the Green-Ampt procedure delivered better results. In this comparison, both procedures used the same initial abstractions. The separation of rainfall losses into infiltration, interception, and surface retention is, in theory, an accurate method of estimating precipitation excess. In the second phase of the study using nine watersheds and 39 storms, interception and surface retention losses were computed by the Horton equations. Green-Ampt and interception parameters were estimated from value sin the literature, while the surface retention parameter was calibrated so that the computed runoff volumes matched observed volumes. A relationship was found between the surface retention storage capacity and the 15-day antecedent precipitation index, month of year, and precipitation amount.     

Stochastic Transfer Function Model and Neural Networks to Estimate Soil Moisture1

Abstract: A practical methodology is proposed to estimate the three‐dimensional variability of soil moisture based on a stochastic transfer function model, which is an approximation of the Richard’s equation. Satellite, radar and in situ observations are the major sources of information to develop a model that represents the dynamic water content in the soil. The soil‐moisture observations were collected from 17 stations located in Puerto Rico (PR), and a sequential quadratic programming algorithm was used to estimate the parameters of the transfer function (TF) at each station. Soil texture information, terrain elevation, vegetation index, surface temperature, and accumulated rainfall for every grid cell were input into a self‐organized artificial neural network to identify similarities on terrain spatial variability and to determine the TF that best resembles the properties of a particular grid point. Soil moisture observed at 20 cm depth, soil texture, and cumulative rainfall were also used to train a feedforward artificial neural network to estimate soil moisture at 5, 10, 50, and 100 cm depth. A validation procedure was implemented to measure the horizontal and vertical estimation accuracy of soil moisture. Validation results from spatial and temporal variation of volumetric water content (vwc) showed that the proposed algorithm estimated soil moisture with a root mean squared error (RMSE) of 2.31% vwc, and the vertical profile shows a RMSE of 2.50% vwc. The algorithm estimates soil moisture in an hourly basis at 1 km spatial resolution, and up to 1 m depth, and was successfully applied under PR climate conditions.     

Developing an Ecosystem Perspective from Experimental Monitoring Programs: I. Demographic Responses of a Rare Geothermal Grass to Soil Temperature

The geysers panic grass [Dichanthelium lanuginosum Spellenberg var. thermale (Bol.) Spellenberg or DILA] is exclusively associated with surface geothermal manifestations in Sonoma County, California, USA (38°46′N, 122°38′W). Steam extraction by power plants could alter the subsurface distribution of heat and water to the site, potentially impacting subpopulations of this rare plant. The purpose of this study was to use demographic monitoring to determine: (1) temporal and spatial patterns of soil temperature in relation to the distribution of established DILA individuals at Little Geysers, (2) in situ response of experimental populations of DILA to spatial variations in soil temperature, and (3) habitat requirements of DILA as an indicator of its tolerance to variations in surficial geothermal features. Thermocouple transects and a datalogger provided data for characterizing the spatial and temporal patterns of soil temperature in four microhabitats (fumarole, DILA stand, Andropogon stand, and cleared). Experimental populations were established by precisely sowing and monitoring DILA seeds in these microhabitats. The results indicated that spatial and temporal variations in soil temperature had significant effects on the processes of germination, growth, survivorship, and reproduction, thus producing a readily observed metapopulation patch dynamic in relation to geothermal activity. Seasonal depressions of soil temperature near the fumaroles by cold air and prolonged rainfall events also promoted the emergence and survival of DILA seedlings in a microhabitat that was previously too hot to occupy. Over longer periods of time, DILA metapopulation dynamism reflected climatic and geothermal variation. Drought years inhibited germination for lack of water, but more importantly for the lack of requisite soil temperature depressions in the fumarole microhabitat. Wet years promoted subpopulation expansion into transition areas that were once too hot and dry. There have also been shifts in the underground distribution of steam into areas distant from known geothermal features. The demographic responses of DILA to spatial and temporal variations in soil temperature indicate that heat is an absolutely essential component of the steam resource. In its absence, germination, seeding survivorship, growth, and maturation are significantly inhibited even if soil conditions are favorable and potential competitors are controlled. Ultimately, persistence of the species depends on maintaining the ecosystem dynamic of colonization and extirpation in response to variations in surficial geothermal features over long spatial and temporal scales. This should shift management perspective from its narrow focus on individual plants to a wider focus on monitoring the essential habitat component of steam.     

Life Cycle Assessment of a Wastewater Treatment Plant Focused on Material and Energy Flows

Life cycle assessment (LCA) was applied to analyze a food-processing wastewater treatment plant and investigate the economic and environmental effects of the plant. With the long-term operational data of this plant, an inventory of relative inputs, e.g., flow rate, chemical oxygen demand (COD), and suspended solids, etc., and outputs of the plant, e.g., effluent COD and suspended solids, methane production, etc., was compiled. The potential environmental effects associated with those inputs and outputs were evaluated, and the results of the inventory analysis and impact assessment phases of the plant were interpreted. One feature of this study was the assessment of the treatment plant based on both energy and material flows. Another feature was the establishment of an assessment model with an integration of plant operating parameters, system recognition and grey relation. The analytical results are helpful for the design and operation of wastewater treatment plants.     

EVAPOTRANSPIRATION CONCEPTUALIZATION IN THE HSPF‐MODFLOW INTEGRATED MODELS1

In 1988, the Florida Institute of Phosphate Research (FIPR) funded project to develop an advanced hydrologic model for shallow water table systems. The FIPR hydrologic model (FHM) was developed to provide an improved predictive capability of the interactions of surface water and ground water using its component models, HSPF and MODFLOW. The Integrated Surface and Ground Water (ISGW) model was developed from an early version of FHM and the two models were developed relatively independently in the late 1990s. Hydrologic processes including precipitation, interception, evapotranspiration, runoff, recharge, streamflow, and base flow are explicitly accounted for in both models. Considerable review of FHM and ISGW and their applications occurred through a series of projects. One model evolved, known as the Integrated Hydrological Model IHM. This model more appropriately describes hydrologic processes, including evapotranspiration fluxes within small distributed land‐based discretization. There is a significant departure of many IHM algorithms from FHM and ISGW, especially for soil water and evapotranspiration (ET). In this paper, the ET concepts in FHM, ISGW, and IHM will be presented. The paper also identifies the advantages and data costs of the improved methods. In FHM and IHM, ground water ET algorithms of the MODFLOW ET package replace those of HSPF (ISGW used a different model for ground water ET). However, IHM builds on an improved understanding and characterization of ET partitioning between surface storages, vadose zone storage, and saturated ground water storage. The IHM considers evaporative flux from surface sources, proximity of the water table to land surface, relative moisture condition of the unsaturated zone, thickness of the capillary zone, thickness of the root zone, and relative plant cover density. The improvements provide a smooth transition to satisfy ET demand between the vadose zone and deeper saturated ground water. While the IHM approach provides a more sound representation of the actual soil profile than FHM, and has shown promise at reproducing soil moisture and water table fluctuations as well as field measured ET rates, more rigorous testing is necessary to understand the robustness and/or limitations of this methodology.     

Variation in Vegetation Structure and Soil Properties, and the Relation Between Understory Plants and Environmental Variables Under Different Phyllostachys pubescens Forests in Southeastern China

Biodiversity maintenance and soil improvement are key sustainable forestry objectives. Research on the effects of bamboo forest management on plant diversity and soil properties are therefore necessary in bamboo-growing regions, such as southeastern China’s Shunchang County, that have not been studied from this perspective. We analyzed the effects of different Phyllostachys pubescens proportions in managed forests on vegetation structure and soil properties using pure Cunninghamia lanceolata forests as a contrast, and analyzed the relation between understory plants and environmental variables (i.e., topography, stand and soil characteristics) by canonical correspondence analysis (CCA). The forest with 80% P. pubescens and 20% hardwoods (such as Phoebe bournei, Jatropha curcas, Schima superba) maintained the highest plant diversity and best soil properties, with significantly higher plant diversity than the C. lanceolata forest, and better soil physicochemical and biological properties. The distribution of understory plants is highly related to environmental factors. Silvicultural disturbance strongly influenced the ability of different bamboo forests to maintain biodiversity and soil quality under extensive management, and the forest responses to management were consistent with the intermediate-disturbance hypothesis (i.e., diversity and soil properties were best at intermediate disturbance levels). Our results suggest that biodiversity maintenance and soil improvement are important management goals for sustainable bamboo management. To achieve those objectives, managers should balance the inputs and outputs of nutrients and protect understory plants by using appropriate fertilizer (e.g., organic fertilizer), adjusting stand structure, modifying utilization model and the harvest time, and controlling the intensity of culms and shoots harvests.     

Environmental indices in irrigation management

Irrigation management calls for objective criteria capable of representing the economy, reliability, and productivity of irrigation systems. These criteria must be compatible with long-term sustainability and conservation goals. The criteria representing the above goals are the economic effect of management on yield reduction, economic effect, and reliability referring to plant growth and operation of the network. In this study environmental indices are introduced to express the above criteria in quantitative terms. The inclusion of these indices at the farm and network level create a multicriteria framework for decision-making based on composite programming. An experimental study was conducted during the irrigation periods of 1989 and 1990 in Chania, Greece, concerning water delivered to 40 experimental plots, soil moisture content at the rootzone, and irrigation system operational failures. The data collected in real time were used for the calculation of the corresponding environmental indices. The variation in time and space is high and resulted in up to 62% of yield loss and low system performance (up to 7% of system temporal reliability). The study indicated that environmental indices could be incorporated to select alternatives and also to develop policies on water delivery. The final decision involves a trade-off analysis between cost of application and desired system performance. Measures of both primary objectives can be obtained using environmental indices that represent system operation aggregation at its basic levels (on farm and network).     

A REVISED VERSION OF PnET‐II TO SIMULATE THE HYDROLOGIC CYCLE IN SOUTHEASTERN FORESTED AREAS1

ABSTRACT: The PnET‐II model uses hydroclimatic data on maximum and minimum temperatures, precipitation, and solar radiation, together with vegetation and soil parameters, to produce estimates of net primary productivity, evapotranspiration (ET), and runoff on a monthly time step for forested areas. In this study, the PnET‐II model was employed to simulate the hydrologic cycle for 17 Southeastern eight‐digit hydrologic unit code (HUC) watersheds dominated by evergreen or deciduous tree species. Based on these control experiments, model biases were quantified and tentative revision schemes were introduced. Revisions included: (1) replacing the original single soil layer with three soil layers in the water balance routine; (2) introducing calibrating factors to rectify the phenomenon of overestimation of ET in spring and early summer months; (3) parameterizing proper values of growing degree days for trees located in different climate zones; and (4) adjusting the parameter of fast‐flow (overland flow) fraction based on antecedent moisture condition and precipitation intensity. The revised PnET‐II model, called PnET‐II3SL in this work, substantially improved runoff simulations for the 17 selected experimental sites, and therefore may offer a more powerful tool to address issues in water resources management.     

Pre-combustion CO2 capture from natural gas power plants,with ATR and MDEA processes

Among the various configurations of fossil fuel power plants with carbon capture, this paper focuses on pre-combustion techniques applied to natural gas combined cycles. With more detail, the plant configuration here addressed includes: (i) the steam reforming of natural gas, based on an air-blown autothermal process, following a recuperative pre-reforming treatment, (ii) the water gas shift producing CO₂ and H₂, (iii) the separation of CO₂ by means of a mixed physical–chemical absorption system using a MDEA solution, and (iv) a hydrogen fuelled combined cycle.Similar configurations have been studied quite extensively, being among the most attractive for full-scale realizations in a near-mid term future. This paper proposes a detailed thermodynamic study and optimization of the plant configuration, bringing to a reliable performance estimation based on today's best available technology as far as the various plant sections are concerned (gas and steam turbine, natural gas reforming process, CO₂ separation). The predicted LHV efficiency for the base configuration is about 50%. Being this value at the top of the range quoted in the open literature studies (35–50%), the paper includes a quite extensive sensitivity analysis, showing that more conservative assumptions may bring to significantly poorer performance, especially considering the pretty large number of operating parameters involved in the process.     

Does the Temporal Resolution of Precipitation Input Influence the Simulated Hydrological Components Employing the SWAT Model?

This study aimed to evaluate the influence of sub‐daily precipitation time steps on model performance and hydrological components by applying the Green and Ampt infiltration method using the Soil and Water Assessment Tool (SWAT). Precipitation was measured at a resolution of 0.1 mm and aggregated to 5‐, 15‐, 30‐, and 60‐min time steps. Daily discharge data over a 10‐year period were used to calibrate and validate the model. Following a global sensitivity analysis, relevant parameters were optimized through an automatic calibration procedure using SWAT‐CUP for each time step. Daily performance statistics were almost equal among all four time steps (NSE ≈ 0.47). Discharge mainly consisted of groundwater flow (55%) and tile flow (42%), in reasonable proportions for the investigated catchment. In conclusion, model outputs were almost identical, showing simulations responded nearly independently of the chosen precipitation time step. This held true for (1) the selection of sensitive parameters, (2) performance statistics, (3) the shape of the hydrographs, and (4) flow components. However, a scenario analysis revealed that the precipitation time step becomes important when saturated hydraulic conductivities are low and curve numbers are high. The study suggests that there is no need in using precipitation time steps <1 h for lowland catchments dominated by soils with a low surface runoff potential if daily flow values are being considered. Editor's note : This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.