Crops as sensors: Using crop yield data to increase the robustness of hydrologic and biogeochemical models
TL;DR: In this article, a hydrologic model using the Soil and Water Assessment Tool was used to identify the proper model structure and improve the robustness of the hydrological model, and the modified model was able to better capture variations in nitrate loads at the catchment outlet with no calibration.
About: This article is published in Journal of Hydrology.The article was published on 2021-01-01. It has received 8 citations till now. The article focuses on the topics: Hydrological modelling & Streamflow.
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TL;DR: In this article, the authors identify systemic change and its possible causes with the PCR-GLOBWB hydrological model in the Rhine-Meuse basin, by performing a brute-force calibration for multiple periods for five calibration locations between 1901-2010.
6 citations
TL;DR: In this article , the authors assess the predictive uncertainty of the Soil and Water Assessment Tool (SWAT), depending on the inclusion or exclusion of annual crop yield as an additional constraint for an agricultural watershed.
4 citations
TL;DR: In this article , the impact of three calibration methods (SQN, SML and SQN_SML) on model performance and parameter uncertainty in the Kantamal catchment of the Mahanadi basin, India was investigated.
Abstract: Spatially distributed watershed models are commonly utilized to address a wide range of water-related issues. However, setting up a reliable watershed model is a difficult task involving several essential decisions making. Choice of calibration method is one of the most important decisions that has been sparsely investigated in semi-distributed watershed models. In this study, therefore, we used the Soil and Water Assessment Tool (SWAT) model to investigate the impact of three calibration methods: sequential (SQN), simultaneous (SML) and sequential-simultaneous (SQN_SML) on model performance and parameter uncertainty in the Kantamal catchment of the Mahanadi basin, India. The findings across the calibration methods; evaluated fit scores of streamflow for respective calibration and validation period; showed that SQN_SML calibration has the least amount of bias (PBAIS = 1.7, −4.2), the highest NSE (0.91, 0.92), KGE (0.95, 0.94) and R2 (0.91, 0.92). Furthermore, SQN_SML outperformed the other two methods in all three streamflow regimes (low, medium and high) of flow duration curve analysis. Suspended sediment load (SSL) analyses of partitioned sediment duration curve showed the best performance of SQN_SML for mid and low SSL regimes while all three calibration methods performed similarly in the high SSL regime. SML calibration approach showed the least parameter uncertainty followed by SQN_SML and SQN. The P-factor for sediment simulation was better for the SQN_SML approach, indicating the minimal model error for sediment simulation. The SQN_SML produced the least equifinal solution, while the SQN approach produced the highest equifinal solution. Overall, the findings of this study may help the watershed modelling communities for selecting suitable calibration strategies when dealing with integrated water resources management.
3 citations
TL;DR: In this paper, the authors explored the use of satellite-based Land Use Land Cover (LULC) data while simultaneously correcting potential evapotranspiration (PET) input with leaf area index (LAI) to increase the performance of a physically distributed hydrologic model.
Abstract: Effective management of water resources entails the understanding of spatiotemporal changes in hydrologic fluxes with variation in land use, especially with a growing trend of urbanization, agricultural lands and non-stationarity of climate. This study explores the use of satellite-based Land Use Land Cover (LULC) data while simultaneously correcting potential evapotranspiration (PET) input with Leaf Area Index (LAI) to increase the performance of a physically distributed hydrologic model. The mesoscale hydrologic model (mHM) was selected for this purpose due to its unique features. Since LAI input informs the model about vegetation dynamics, we incorporated the LAI based PET correction option together with multi-year LULC data. The Globcover land cover data was selected for the single land cover cases, and hybrid of CORINE (coordination of information on the environment) and MODIS (Moderate Resolution Imaging Spectroradiometer) land cover datasets were chosen for the cases with multiple land cover datasets. These two datasets complement each other since MODIS has no separate forest class but more frequent (yearly) observations than CORINE. Calibration period spans from 1990 to 2006 and corresponding NSE (Nash-Sutcliffe Efficiency) values varies between 0.23 and 0.42, while the validation period spans from 2007 to 2010 and corresponding NSE values are between 0.13 and 0.39. The results revealed that the best performance is obtained when multiple land cover datasets are provided to the model and LAI data is used to correct PET, instead of default aspect-based PET correction in mHM. This study suggests that to minimize errors due to parameter uncertainties in physically distributed hydrologic models, adequate information can be supplied to the model with care taken to avoid over-parameterizing the model.
3 citations
Cites background from "Crops as sensors: Using crop yield ..."
...[18], which further clarified the need for additional calibration data sources to improve the robustness and predictive ability of distributed models....
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DOI•
TL;DR: In this paper , a mesoscale catchment N model was proposed to disentangle contrasting agri-environment functional mechanisms in typically flashy chemodynamic and transport-limited chemostatic export regimes.
Abstract: Diffuse Nitrogen pollution from agriculture maintains high pressures on groundwater and aquatic ecosystems. Further mitigation requires targeted measures that reconcile agricultural interests in environmental protection. However, the agriculture‐related processes of catchment N modeling remain poorly defined due to discipline‐specific data and knowledge gaps. Using field‐experimental data, crop N uptake responses to fertilizer management were parsimoniously conceptualized and integrated into a catchment diffuse‐N model. The improved catchment modeling further facilitated integration with agricultural budget‐based assessments. The integrated analysis in a mesoscale catchment disentangled contrasting agri‐environment functional mechanisms in typically flashy chemodynamic and transport‐limited chemostatic export regimes. Moreover, the former was actively responsive to interannual climatic variability and agricultural practices; the latter exhibited drought‐induced enhancement of N enrichment, which could likely be mitigated through reduced fertilization. This interdisciplinary integration of data and methods provided an insightful evidence base for multi‐sector targeted measures, especially under cumulative impacts of changing climate and fertilizer‐use intensities.
2 citations
References
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TL;DR: The GLUE procedure works with multiple sets of parameter values and allows that, within the limitations of a given model structure and errors in boundary conditions and field observations, different sets of values may be equally likely as simulators of a catchment.
Abstract: This paper describes a methodology for calibration and uncertainty estimation of distributed models based on generalized likelihood measures. The GLUE procedure works with multiple sets of parameter values and allows that, within the limitations of a given model structure and errors in boundary conditions and field observations, different sets of values may be equally likely as simulators of a catchment. Procedures for incorporating different types of observations into the calibration; Bayesian updating of likelihood values and evaluating the value of additional observations to the calibration process are described. The procedure is computationally intensive but has been implemented on a local parallel processing computer.
4,146 citations
TL;DR: The argument is made that the potential for multiple acceptable models as representations of hydrological and other environmental systems (the equifinality thesis) should be given more serious consideration than hitherto.
2,073 citations
TL;DR: The generalised likelihood uncertainty estimation (GLUE) methodology for model identification allowing for equifinality is described, and an example application to rainfall-runoff modelling is used to illustrate the methodology, including the updating of likelihood measures.
1,977 citations
Journal Article•
1,793 citations
TL;DR: In this paper, the authors used the SWAT (Soil and Water Assessment Tool) to simulate all related processes affecting water quantity, sediment, and nutrient loads in the Thur River basin, which is a direct tributary to the Rhine.
1,571 citations