scholarly journals Assessment of Streamflow Simulation for a Tropical Forested Catchment Using Dynamic TOPMODEL—Dynamic fluxEs and ConnectIvity for Predictions of HydRology (DECIPHeR) Framework and Generalized Likelihood Uncertainty Estimation (GLUE)

Water ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 317
Author(s):  
Fadhliani Umar ◽  
Zed Zulkafli ◽  
Badronnisa Yusuf ◽  
Siti Nurhidayu
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Peak Flow ◽  
Uncertainty Estimation ◽  
Model Parameters ◽  
Model Framework ◽  
Behavioral Threshold ◽  
Continuous Simulation ◽  
Generalized Likelihood Uncertainty Estimation ◽  
Streamflow Simulation

Rainfall runoff modeling has been a subject of interest for decades due to a need to understand a catchment system for management, for example regarding extreme event occurrences such as flooding. Tropical catchments are particularly prone to the hazards of extreme precipitation and the internal drivers of change in the system, such as deforestation and land use change. A model framework of dynamic TOPMODEL, DECIPHeR v1—considering the flexibility, modularity, and portability—and Generalized Likelihood Uncertainty Estimation (GLUE) method are both used in this study. They reveal model performance for the streamflow simulation in a tropical catchment, i.e., the Kelantan River in Malaysia, that is prone to flooding and experiences high rates of land use change. Thirty-two years’ continuous simulation at a daily time scale simulation along with uncertainty analysis resulted in a Nash Sutcliffe Efficiency (NSE) score of 0.42 from the highest ranked parameter set, while 25.35% of the measurement falls within the uncertainty boundary based on a behavioral threshold NSE 0.3. The performance and behavior of the model in the continuous simulation suggests a limited ability of the model to represent the system, particularly along the low flow regime. In contrast, the simulation of eight peak flow events achieves moderate to good fit, with the four peak flow events simulation returning an NSE > 0.5. Nonetheless, the parameter scatter plot from both the continuous simulation and analyses of peak flow events indicate unidentifiability of all model parameters. This may be attributable to the catchment modeling scale. The results demand further investigation regarding the heterogeneity of parameters and calibration at multiple scales.

scholarly journals Assessment of Streamflow Simulation for a Tropical Forested Catchment using Dynamic TOPMODEL – Dynamic fluxEs and ConnectIvity for Predictions of HydRology (DECIPHeR) Framework and Generalized Likelihood Uncertainty Estimation (GLUE)

2020 ◽  
Author(s):  
Fadhliani Umar ◽  
Zed Diyana ◽  
Badronnisa Yusuf ◽  
Siti Nurhidayu
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Peak Flow ◽  
Uncertainty Estimation ◽  
Model Parameters ◽  
Model Framework ◽  
Behavioral Threshold ◽  
Continuous Simulation ◽  
Generalized Likelihood Uncertainty Estimation ◽  
Streamflow Simulation

Rainfall runoff modeling has been a subject of interest for decades due to a need to understand a catchment system for management, for example regarding extreme event occurrences such as flooding. Tropical catchments are particularly prone to the hazards of extreme precipitation and the internal drivers of change in the system, such as deforestation and land use change. A model framework of dynamic TOPMODEL, DECIPHeR v1 - considering the flexibility, modularity and portability - and Generalized Likelihood Uncertainty Estimation (GLUE) method are both used in this study. They reveal model performance for the streamflow simulation in a tropical catchment, i.e. the Kelantan River in Malaysia, that is prone to flooding and experiences high rates of land use change. 32 years' continuous simulation at a daily time scale simulation along with uncertainty analysis resulted in a Nash Sutcliffe Efficiency (NSE) score of 0.42 from the highest ranked parameter set, while 25.35% of the measurement falls within the uncertainty boundary based on a behavioral threshold NSE 0.3. The performance and behavior of the model in the continuous simulation suggests a limited ability of the model to represent the system, particularly along the low flow regime. In contrast, the simulation of eight peak flow events achieves moderate to good fit, with the four peak flow events simulation returning an NSE > 0.5. Nonetheless, the parameter scatterplot from both the continuous simulation and analyses of peak flow events indicate unidentifiability of all model parameters. This may be attributable to the catchment modelling scale. The results demand further investigation regarding the heterogeneity of parameters and calibration at multiple scales.

scholarly journals Grassland production under global change scenarios for New Zealand pastoral agriculture

2014 ◽  
Vol 7 (5) ◽  
pp. 2359-2391 ◽  
Author(s):  
E. D. Keller ◽  
W. T. Baisden ◽  
L. Timar ◽  
B. Mullan ◽  
A. Clark
Keyword(s):  
Climate Change ◽  
Land Use ◽  
New Zealand ◽  
Land Use Change ◽  
Model Parameters ◽  
Agricultural Activity ◽  
High Fertility ◽  
Climate Change Scenarios ◽  
Pasture Production ◽  
N Cycle

Abstract. We adapt and integrate the Biome-BGC and Land Use in Rural New Zealand models to simulate pastoral agriculture and to make land-use change, intensification of agricultural activity and climate change scenario projections of New Zealand's pasture production at time slices centred on 2020, 2050 and 2100, with comparison to a present-day baseline. Biome-BGC model parameters are optimised for pasture production in both dairy and sheep/beef farm systems, representing a new application of the Biome-BGC model. Results show up to a 10% increase in New Zealand's national pasture production in 2020 under intensification and a 1–2% increase by 2050 from economic factors driving land-use change. Climate change scenarios using statistically downscaled global climate models (GCMs) from the IPCC Fourth Assessment Report also show national increases of 1–2% in 2050, with significant regional variations. Projected out to 2100, however, these scenarios are more sensitive to the type of pasture system and the severity of warming: dairy systems show an increase in production of 4% under mild change but a decline of 1% under a more extreme case, whereas sheep/beef production declines in both cases by 3 and 13%, respectively. Our results suggest that high-fertility systems such as dairying could be more resilient under future change, with dairy production increasing or only slightly declining in all of our scenarios. These are the first national-scale estimates using a model to evaluate the joint effects of climate change, CO2 fertilisation and N-cycle feedbacks on New Zealand's unique pastoral production systems that dominate the nation's agriculture and economy. Model results emphasise that CO2 fertilisation and N-cycle feedback effects are responsible for meaningful differences in agricultural systems. More broadly, we demonstrate that our model output enables analysis of decoupled land-use change scenarios: the Biome-BGC data products at a national or regional level can be re-sampled quickly and cost-effectively for specific land-use change scenarios and future projections.

scholarly journals Combined effects of predicted climate and land use changes on future hydrological droughts in the Luanhe River basin, China

2021 ◽  
Author(s):  
Xu Chen ◽  
Ruiguang Han ◽  
Yongjie Wang
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Land Use Change ◽  
River Basin ◽  
Emission Scenario ◽  
Land Use Changes ◽  
Model Parameters ◽  
Baseline Scenario ◽  
Luanhe River Basin ◽  
Hydrological Droughts

Abstract Drought can be impacted by both climate change and land use change in different ways. Thus, in order to predict future drought conditions, hydrological simulations as an ideal means, can be used to account for both projected climate change and projected land use change. In this study, projected climate and land use changes were integrated with the SWAT (Soil and Water Assessment Tool) model to estimate the combined impact of climate and land use projections on hydrological droughts in the Luanhe River basin. We presented that the measured runoff and the remote sensing inversion of soil water content were simultaneously used to validate the model to ensure the reliability of model parameters. Following the calibration and validation, the SWAT model was forced with downscaled precipitation and temperature outputs from a suite of nine Global Climate Models (GCMs) based on the CMIP5, corresponding to three different representative concentration pathways (RCP 2.6, RCP 4.5 and 8.5) for three distinct time periods: 2011–2040, 2041–2070 and 2071–2100, referred to as early-century, mid-century and late-century, respectively, and the land use predicted by CA-Markov model in the same future periods. Hydrological droughts were quantified using the Standardized Runoff Index (SRI). Compared to the baseline scenario (1961–1990), mild drought occurred more frequently during the next three periods (except the 2080s under the RCP2.6 emission scenario). Under the RCP8.5 emission scenario, the probability of severe drought or above occurring in the 2080s increased, the duration prolonged and the severity increased. Under the RCP2.6 scenario, the upper central region of the Luanhe river in the 2020s and upper reaches of the Luanhe river in the 2080s, were more likely to suffer extreme drought events. And under the RCP8.5 scenario, the middle and lower Luanhe river in the 2080s, were more likely to suffer these conditions.

scholarly journals Grassland production under global change scenarios for New Zealand pastoral agriculture

2014 ◽  
Vol 7 (3) ◽  
pp. 3307-3365
Author(s):  
E. D. Keller ◽  
W. T. Baisden ◽  
L. Timar ◽  
B. Mullan ◽  
A. Clark
Keyword(s):  
Climate Change ◽  
Land Use ◽  
New Zealand ◽  
Land Use Change ◽  
Global Climate Models ◽  
Model Parameters ◽  
High Fertility ◽  
Climate Change Scenarios ◽  
Pasture Production ◽  
N Cycle

Abstract. We adapt and integrate the Biome-BGC and Land Use in Rural New Zealand (LURNZ) models to simulate pastoral agriculture and to make land-use change, intensification and climate change scenario projections of New Zealand's pasture production at time slices centred on 2020, 2050 and 2100, with comparison to a present-day baseline. Biome-BGC model parameters are optimised for pasture production in both dairy and sheep/beef farm systems, representing a new application of the Biome-BGC model. Results show up to a 10% increase in New Zealand's national pasture production in 2020 under intensification and a 1–2% increase by 2050 from economic factors driving land-use change. Climate change scenarios using statistically downscaled global climate models (GCMs) from the IPCC Fourth Assessment Report (AR4) also show national increases of 1–2% in 2050, with significant regional variations. Projected out to 2100, however, these scenarios are more sensitive to the type of pasture system and the severity of warming: dairy systems show an increase in production of 4% under mild change but a decline of 1% under a more extreme case, whereas sheep/beef production declines in both cases by 3% and 13%, respectively. Our results suggest that high-fertility systems such as dairying could be more resilient under future change, with dairy production increasing or only slightly declining in all of our scenarios. These are the first national-scale estimates using a model to evaluate the joint effects of climate change, CO2 fertilisation and N-cycle feedbacks on New Zealand's unique pastoral production systems that dominate the nation's agriculture and economy. Model results emphasize that CO2 fertilisation and N cycle feedback effects are responsible for meaningful differences in agricultural systems. More broadly, we demonstrate that our model output enables analysis of Decoupled Land-Use Change Scenarios (DLUCS): the Biome-BGC data products at a national or regional level can be re-sampled quickly and cost-effectively for specific land-use change scenarios and future projections.

scholarly journals Anomaly in the rainfall-runoff behaviour of the Meuse catchment. Climate, land use, or land use management?

2008 ◽  
Vol 5 (4) ◽  
pp. 1787-1819 ◽  
Author(s):  
F. Fenicia ◽  
H. H. G. Savenije ◽  
Y. Avdeeva
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Land Cover ◽  
Climatic Variability ◽  
Time Lag ◽  
Temporal Trends ◽  
Model Parameters ◽  
Land Use Management ◽  
Rainfall Runoff ◽  
The Way

Abstract. An anomaly has been found in the rainfall runoff behaviour of the Meuse. Ninety years of rainfall-runoff simulations show a consistent underestimation of the runoff in the period between 1930 and 1965. Different authors have debated possible causes for the anomaly, including climatic variability, land use change and data errors. None of the authors considered the way in which the land is used by for instance agricultural and forestry practises. This paper focuses on the possible effects of land use and land use management on the hydrological response of the Meuse catchment. In absence of detailed information on land use over the observation period, we adopted a fully "top-down" approach to the problem. The approach consists of a dynamic evaluation of a conceptual hydrological model and the interpretation of the temporal trends of model parameters. It appears that land use has had a considerable impact on the hydrological behaviour of the Meuse catchment. The time lag of the catchment has reduced markedly over time, possibly related to more intensive drainage and river training works. Moreover we hypothesise that forest rotation has had a significant impact on the evaporation of the catchment. These results contrast with previous studies, where the effect of land use change on the hydrological behaviour of the Meuse catchment was considered negligible, mainly because there was not sufficient change in land cover to account for it. Here we hypothesise that in the Meuse it was not the change of land cover that was responsible for hydrological change, but rather the way the land was managed.

scholarly journals A model-based constraint of CO<sub>2</sub> fertilisation

2012 ◽  
Vol 9 (7) ◽  
pp. 9425-9451 ◽  
Author(s):  
P. B. Holden ◽  
N. R. Edwards ◽  
D. Gerten ◽  
S. Schaphoff
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Co2 Concentration ◽  
Earth System Model ◽  
Atmospheric Co2 ◽  
System Model ◽  
Model Parameters ◽  
Earth System ◽  
Atmospheric Co2 Concentration ◽  
Post Industrial

Abstract. We derive a constraint on the strength of CO2 fertilisation of the terrestrial biosphere through a "top-down" approach, calibrating Earth System Model parameters constrained only by the post-industrial increase of atmospheric CO2 concentration. We derive a probabilistic prediction for the globally averaged strength of CO2 fertilisation in nature, implicitly net of other limiting factors such as nutrient availability. The approach yields an estimate that is independent of CO2 enrichment experiments and so provides a new constraint that can in principal be combined with data-driven priors. To achieve this, an essential requirement was the incorporation of a Land Use Change (LUC) scheme into the GENIE earth system model, which we describe in full. Using output from a 671-member ensemble of transient GENIE simulations we build an emulator of the change in atmospheric CO2 concentration change over the preindustrial period (1850 to 2000). We use this emulator to sample the 28-dimensional input parameter space. A Bayesian calibration of the emulator output suggests that the increase in Gross Primary Productivity in response of a doubling of CO2 from preindustrial values is likely to lie in the range 11 to 53%, with a most likely value of 28%. The present-day land-atmosphere flux (1990–2000) is estimated at −0.6 GTC yr−1 (likely in the range 0.9 to −2.0 GTC yr−1). The present-day land-ocean flux (1990–2000) is estimated at −2.2 GTC yr−1 (likely in the range −1.6 to −2.8 GTC yr−1). We estimate cumulative net land emissions over the post-industrial period (land use change emissions net of the CO2 fertilisation sink) to be 37 GTC, likely to lie in the range 130 to −20 GTC.

scholarly journals Time-varying parameter models for catchments with land use change: the importance of model structure

2018 ◽  
Vol 22 (5) ◽  
pp. 2903-2919 ◽  
Author(s):  
Sahani Pathiraja ◽  
Daniela Anghileri ◽  
Paolo Burlando ◽  
Ashish Sharma ◽  
Lucy Marshall ◽  
...  
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Land Cover ◽  
Parameter Estimates ◽  
Parameter Method ◽  
Model Parameters ◽  
Model Structure ◽  
Time Varying ◽  
Time Varying Parameter ◽  
Invariant Parameter

Abstract. Rapid population and economic growth in Southeast Asia has been accompanied by extensive land use change with consequent impacts on catchment hydrology. Modeling methodologies capable of handling changing land use conditions are therefore becoming ever more important and are receiving increasing attention from hydrologists. A recently developed data-assimilation-based framework that allows model parameters to vary through time in response to signals of change in observations is considered for a medium-sized catchment (2880 km2) in northern Vietnam experiencing substantial but gradual land cover change. We investigate the efficacy of the method as well as the importance of the chosen model structure in ensuring the success of a time-varying parameter method. The method was used with two lumped daily conceptual models (HBV and HyMOD) that gave good-quality streamflow predictions during pre-change conditions. Although both time-varying parameter models gave improved streamflow predictions under changed conditions compared to the time-invariant parameter model, persistent biases for low flows were apparent in the HyMOD case. It was found that HyMOD was not suited to representing the modified baseflow conditions, resulting in extreme and unrealistic time-varying parameter estimates. This work shows that the chosen model can be critical for ensuring the time-varying parameter framework successfully models streamflow under changing land cover conditions. It can also be used to determine whether land cover changes (and not just meteorological factors) contribute to the observed hydrologic changes in retrospective studies where the lack of a paired control catchment precludes such an assessment.

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