Understanding nitrogen transfer dynamics in a small agricultural catchment: Comparison of a distributed (TNT2) and a semi distributed (SWAT) modeling approaches

The coupling of an hydrological and a crop model is an efficient approach to study the impact of the interactions between agricultural practices and catchment physical characteristics on stream water quality. We analyzed the consequences of using different modeling approaches of the processes controlling the nitrogen (N) dynamics in a small agricultural catchment monitored for 15 years. Two agro-hydrological models were applied: the fully distributed model TNT2 and the semi-distributed SWAT model. Using the same input dataset, the calibration process aimed at reproducing the same annual water and N balance in both models, to compare the spatial and temporal variability of the main N processes. The models simulated different seasonal cycles for soil N. The main processes involved were N mineralization and denitrification. TNT2 simulated marked seasonal variations with a net increase of mineralization in autumn, after a transient immobilization phase due to the burying of the straw with low C:N ratio. SWAT predicted a steady humus mineralization with an increase when straws are buried and a decrease afterwards. Denitrification was mainly occuring in autumn in TNT2 because of the dynamics of N availability in soil and of the climatic and hydrological conditions. SWAT predicts denitrification in winter, when mineral N is available in soil layers. The spatial distribution of these two processes was different as well: less denitrification in bottom land and close to ditches in TNT2, as a result of N transfer dynamics. Both models simulate correctly global trend and inter-annual variability of N losses in small agricultural catchment when a sufficient amount data is available for calibration. However, N processes and their spatial interactions are simulated very differently, in particular soil mineralization and denitrification. The use of such tools for prediction must be considered with care, unless a proper calibration and validation of the different N processes is carried out

Parallelization of the SUFI2 algorithm: a Windows HPC approach.

The Soil and Water Assessment Tool (SWAT) has been used for evaluating land use changes on water resources worldwide, and like many models, SWAT requires calibration. However, the execution time of these calibrations can be rather long, reducing the time available for proper analysis. This paper presents a Windows approach for calibrating SWAT using a multinodal cluster computer, composed of six computers with i7 processors (3.2 GHz; 12 cores), 8 GB RAM and 1 TB HDD each. The only requirement for this type of cluster is to have 64-bit processors. Our computers were setup with Windows Server HPC 2012 R2, a network switch 10/100, and regular Ethernet cables. We used the SUFI2 algorithm that comes with SWAT-CUP package to perform calibrations with 100 simulations at node level. Calibration runs were configured as follows: 1-12 (1 process interval), and 12-72 (12 processes interval), resulting in 17 runs. Each run was repeated three times, and results are presented as the mean execution time, in order to minimize any influence of resources fluctuations. Results showed that time of execution was reduced by almost half by using nine processes (15 min) in comparison with the one node control (28 min). We observed a linear decrease of execution time from one to nine processes. With additional processes, execution time increased about 23% and stabilized at 80% of the control. All processing is divided into five steps: distribute files (2.24% of all processing time), organize samples (0.89%), run SWAT (47.59%), collect results (46.51%) and cleanup (0.28%)

A comparative analysis of projected impacts of climate change on river runoff from global and catchment-scale hydrological models

We present a comparative analysis of projected impacts of climate change on river runoff from two types of distributed hydrological model, a global hydrological model (GHM) and catchment-scale hydrological models (CHM). Analyses are conducted for six catchments that are global in coverage and feature strong contrasts in spatial scale as well as climatic and development conditions. These include the Liard (Canada), Mekong (SE Asia), Okavango (SW Africa), Rio Grande (Brazil), Xiangu (China) and Harper's Brook (UK). A single GHM (Mac-PDM.09) is applied to all catchments whilst different CHMs are applied for each catchment. The CHMs typically simulate water resources impacts based on a more explicit representation of catchment water resources than that available from the GHM, and the CHMs include river routing. Simulations of average annual runoff, mean monthly runoff and high (Q5) and low (Q95) monthly runoff under baseline (1961-1990) and climate change scenarios are presented. We compare the simulated runoff response of each hydrological model to (1) prescribed increases in global mean temperature from the HadCM3 climate model and (2)a prescribed increase in global-mean temperature of 2oC for seven GCMs to explore response to climate model and structural uncertainty. We find that differences in projected changes of mean annual runoff between the two types of hydrological model can be substantial for a given GCM, and they are generally larger for indicators of high and low flow. However, they are relatively small in comparison to the range of projections across the seven GCMs. Hence, for the six catchments and seven GCMs we considered, climate model structural uncertainty is greater than the uncertainty associated with the type of hydrological model applied. Moreover, shifts in the seasonal cycle of runoff with climate change are presented similarly by both hydrological models, although for some catchments the monthly timing of high and low flows differs.This implies that for studies that seek to quantify and assess the role of climate model uncertainty on catchment-scale runoff, it may be equally as feasible to apply a GHM as it is to apply a CHM, especially when climate modelling uncertainty across the range of available GCMs is as large as it currently is. Whilst the GHM is able to represent the broad climate change signal that is represented by the CHMs, we find, however, that for some catchments there are differences between GHMs and CHMs in mean annual runoff due to differences in potential evaporation estimation methods, in the representation of the seasonality of runoff, and in the magnitude of changes in extreme monthly runoff, all of which have implications for future water management issues

Impacts of DEM resolution and area threshold value uncertainty on the drainage network derived using SWAT

Many hydrological algorithms have been developed to automatically extract drainage networks from DEM, and the D8 algorithm is widely used worldwide to delineate drainage networks and catchments. The simulation accuracy of the SWAT model depends on characteristics of the watershed, and previous studies of DEM resolution and its impacts on drainage network extraction have not generally considered the effects of resolution and threshold value on uncertainty. In order to assess the influence of different DEM resolutions and drainage threshold values on drainage network extraction using the SWAT model, 10 basic watershed regions in China were chosen as case studies to analyse the relationship between extracted watershed parameters and the threshold value. SRTM DEM data at 3 different resolutions were used in this study, and regression analysis for DEM resolution, threshold value and extraction effects was done. The results show that DEM resolution influences the selected flow accumulation threshold value; the suitable flow accumulation threshold value increases as the DEM resolution increases, and shows greater variability for basins with lower drainage densities. The link between drainage area threshold value and stream network extraction results was also examined, and showed a variation trend of power function y = axb between the sub-basin counts and threshold value, i.e., the maximum reach length increases while the threshold value increases, and the minimum reach length shows no relation with the threshold value. The stream network extraction resulting from a 250 m DEM resolution and a 50 000 ha threshold value was similar to the real stream network. The drainage network density and the threshold value also shows a trend of power function y = axb ; the value of b is usually 0.5.Keywords: SWAT, digital elevation model (DEM), watershed delineation, threshold valu

Great Lakes Runoff Intercomparison Project Phase 3: Lake Erie (GRIP-E)

Hydrologic model intercomparison studies help to evaluate the agility of models to simulate variables such as streamflow, evaporation, and soil moisture. This study is the third in a sequence of the Great Lakes Runoff Intercomparison Projects. The densely populated Lake Erie watershed studied here is an important international lake that has experienced recent flooding and shoreline erosion alongside excessive nutrient loads that have contributed to lake eutrophication. Understanding the sources and pathways of flows is critical to solve the complex issues facing this watershed. Seventeen hydrologic and land-surface models of different complexity are set up over this domain using the same meteorological forcings, and their simulated streamflows at 46 calibration and seven independent validation stations are compared. Results show that: (1) the good performance of Machine Learning models during calibration decreases significantly in validation due to the limited amount of training data; (2) models calibrated at individual stations perform equally well in validation; and (3) most distributed models calibrated over the entire domain have problems in simulating urban areas but outperform the other models in validation

A Conceptual Framework for Integration Development of GSFLOW Model: Concerns and Issues Identified and Addressed for Model Development Efficiency

In Coupled Groundwater and Surface-Water Flow (GSFLOW) model, the three-dimensional finite-difference groundwater model (MODFLOW) plays a critical role of groundwater flow simulation, together with which the Precipitation-Runoff Modeling System (PRMS) simulates the surface hydrologic processes. While the model development of each individual PRMS and MODFLOW model requires tremendous time and efforts, further integration development of these two models exerts additional concerns and issues due to different simulation realm, data communication, and computation algorithms. To address these concerns and issues in GSFLOW, the present paper proposes a conceptual framework from perspectives of: Model Conceptualization, Data Linkages and Transference, Model Calibration, and Sensitivity Analysis. As a demonstration, a MODFLOW groundwater flow system was developed and coupled with the PRMS model in the Lehman Creek watershed, eastern Nevada, resulting in a smooth and efficient integration as the hydrogeologic features were well captured and represented. The proposed conceptual integration framework with techniques and concerns identified substantially improves GSFLOW model development efficiency and help better model result interpretations. This may also find applications in other integrated hydrologic modelings

Comparative predictions of discharge from an artificial catchment (Chicken Creek) using sparse data

Ten conceptually different models in predicting discharge from the artificial Chicken Creek catchment in North-East Germany were used for this study. Soil texture and topography data were given to the modellers, but discharge data was withheld. We compare the predictions with the measurements from the 6 ha catchment and discuss the conceptualization and parameterization of the models. The predictions vary in a wide range, e.g. with the predicted actual evapotranspiration ranging from 88 to 579 mm/y and the discharge from 19 to 346 mm/y. The predicted components of the hydrological cycle deviated systematically from the observations, which were not known to the modellers. Discharge was mainly predicted as subsurface discharge with little direct runoff. In reality, surface runoff was a major flow component despite the fairly coarse soil texture. The actual evapotranspiration (AET) and the ratio between actual and potential ET was systematically overestimated by nine of the ten models. None of the model simulations came even close to the observed water balance for the entire 3-year study period. The comparison indicates that the personal judgement of the modellers was a major source of the differences between the model results. The most important parameters to be presumed were the soil parameters and the initial soil-water content while plant parameterization had, in this particular case of sparse vegetation, only a minor influence on the results

Uncertainties in the Hydrological Modelling Using Remote Sensing Data over the Himalayan Region

Himalayas the “roof of the world” are the source of water supply for major South Asian Rivers and fulfill the demand of almost one sixth of world’s humanity. Hydrological modeling poses a big challenge for Himalayan River Basins due to complex topography, climatology and lack of quality input data. In this study, hydrological uncertainties arising due to remotely sensed inputs, input resolution and model structure has been highlighted for a Himalayan Gandak River Basin. Firstly, spatial input DEM (Digital Elevation Model) from two sources SRTM (Shuttle Radar Topography Mission) and ASTER (Advanced Space borne Thermal Emission and Reflection Radiometer) with resolutions 30m, 90m and 30m respectively has been evaluated for their delineation accuracy. The result reveals that SRTM 90m has best performance in terms of least area delineation error (13239.28 km2) and least stream network delineation error. The daily satellite precipitation estimates TRMM 3B42 V7 (Tropical Rainfall Monitoring Mission) and CMORPH (Climate Prediction Center MORPHing Technique) are evaluated for their feasibly over these terrains. Evaluation based on various scores related to visual verification method, Yes/no dichotomous, and continuous variable verification method reveal that TRMM 3B42 V7 has better scores than CMORPH. The effect of DEM resolution on the SWAT (Soil Water Assessment Tool) model outputs has been demonstrated using sixteen DEM grid sizes (40m-1000m). The analysis reveals that sediment and flow are greatly affected by the DEM resolutions (for DEMs>300m). The amount of total nitrogen (TN) and total phosphorous (TP) are found affected via slope and volume of flow for DEM grid size ≥150m. The T-test results are significant for SWAT outputs for grid size >500m at a yearly time step. The SWAT model is accessed for uncertainty during various hydrological processes modeling with different setups/structure. The results reflects that the use of elevation band modeling routine (with six to eight elevation bands) improves the streamflow statistics and water budgets from upstream to downstream gauging sites. Also, the SWAT model represents a consistent pattern of spatiotemporal snow cover dynamics when compared with MODIS data. At the end, the uncertainty in the stream flow simulation for TRMM 3B42 V7 for various rainfall intensity has been accessed with the statistics Percentage Bias (PBIAS) and RSR (RMSE-observations Standard Deviation Ratio). The results found that TRMM simulated streamflow is suitable for moderate (7.5 to 35.4 mm/day) to heavy rainfall intensities (35.5 to 124.4 mm/day). The finding of the present work can be useful for TRMM based studies for water resources management over the similar parts of the world