scholarly journals Modeled forest conversion influences humid tropical watershed hydrology more than projected climate change

2021 ◽  
Author(s):  
Taylor Joyal ◽  
Alexander Fremier ◽  
Jan Boll
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Soil Depth ◽  
Model Performance ◽  
Humid Tropics ◽  
Model Parameters ◽  
Forest Conversion ◽  
Watershed Hydrology ◽  
Mountain Watersheds ◽  
Antecedent Moisture

In the humid tropics, forest conversion and climate change threaten the hydrological function and stationarity of watersheds, particularly in steep terrain. As climate change intensifies, shifting precipitation patterns and expanding agricultural and pastoral land use may effectively reduce the resilience of headwater catchments. Compounding this problem is the limited long-term monitoring in developing countries for planning in an uncertain future. In this paper, we asked which change, climate or land use, more greatly affects stream discharge in humid tropical mountain watersheds? To answer this question, we used the process-based, spatially distributed Soil Moisture Routing model. After first evaluating model performance (Ns = 0.73), we conducted a global sensitivity analysis to identify the model parameters that most strongly influence simulated watershed discharge. In particular, peak flows are most influenced by input model parameters that represent baseflow and shallow subsurface soil pathways while low flows are most sensitive to antecedent moisture, macropore hydraulic conductivity, soil depth and porosity parameters. We then simulated a range of land use and climate scenarios in three mountain watersheds of central Costa Rica. Our results show that deforestation influences streamflow more than altered precipitation and temperature patterns through changes in first-order hydrologic hillslope processes. However, forest conversion coupled with intensifying precipitation events amplifies hydrological extremes, reducing the hydrological resilience to predicted climate shifts in mountain watersheds of the humid tropics. This finding suggests that reforestation can help mitigate the effects of climate change on streamflow dynamics in the tropics including impacts to water availability, flood pulses, channel geomorphology and aquatic habitat associated with altered flow regimes.

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 Land Use Land Cover Changes and Their Effects on Surface Air Temperature in Myanmar and Thailand

2021 ◽  
Vol 13 (19) ◽  
pp. 10942
Author(s):  
Khun La Yaung ◽  
Amnat Chidthaisong ◽  
Atsamon Limsakul ◽  
Pariwate Varnakovida ◽  
Can Trong Nguyen
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Land Cover ◽  
Air Temperature ◽  
Surface Air Temperature ◽  
Forest Conversion ◽  
Land Use Land Cover ◽  
Forest Land ◽  
Lulc Changes ◽  
Average Maximum

Land use land cover (LULC) change is one of the main drivers contributing to global climate change. It alters surface hydrology and energy balance between the land surface and atmosphere. However, its impacts on surface air temperature have not been well understood in a dynamic region of LULC changes like Southeast Asia (SEA). This study quantitatively examined the contribution of LULC changes to temperature trends in Myanmar and Thailand as the typical parts of SEA during 1990–2019 using the “observation minus reanalysis” (OMR) method. Overall, the average maximum, mean, and minimum temperatures obtained from OMR trends indicate significant warming trends of 0.17 °C/10a, 0.20 °C/10a, and 0.42 °C/10a, respectively. The rates of minimum temperature increase were larger than maximum and mean temperatures. The decreases of forest land and cropland, and the expansions of settlements land fractions were strongly correlated with the observed warming trends. It was found that the effects of forest land converted to settlement land on warming were higher than forest conversion to cropland. A comprehensive discussion on this study could provide scientific information for the future development of more sustainable land use planning to mitigate and adapt to climate change at the local and national levels.

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 Technical note: A bootstrapped LOESS regression approach for comparing soil depth profiles

2016 ◽  
Vol 13 (13) ◽  
pp. 3863-3868 ◽  
Author(s):  
Aidan M. Keith ◽  
Peter A. Henrys ◽  
Rebecca L. Rowe ◽  
Niall P. McNamara
Keyword(s):  
Land Use ◽  
Soil Profile ◽  
Soil Depth ◽  
Technical Note ◽  
Model Parameters ◽  
Land Uses ◽  
Parametric Approach ◽  
Soil System ◽  
Depth Profiles ◽  
Non Parametric

Abstract. Understanding the consequences of different land uses for the soil system is important to make better informed decisions based on sustainability. The ability to assess change in soil properties, throughout the soil profile, is a critical step in this process. We present an approach to examine differences in soil depth profiles between land uses using bootstrapped LOESS regressions (BLRs). This non-parametric approach is data-driven, unconstrained by distributional model parameters and provides the ability to determine significant effects of land use at specific locations down a soil profile. We demonstrate an example of the BLR approach using data from a study examining the impacts of bioenergy land use change on soil organic carbon (SOC). While this straightforward non-parametric approach may be most useful in comparing SOC profiles between land uses, it can be applied to any soil property which has been measured at satisfactory resolution down the soil profile. It is hoped that further studies of land use and land management, based on new or existing data, can make use of this approach to examine differences in soil profiles.

scholarly journals The importance of ecosystem adaptation on hydrological model predictions in response to climate change

2021 ◽  
Author(s):  
Laurène J. E. Bouaziz ◽  
Emma E. Aalbers ◽  
Albrecht H. Weerts ◽  
Mark Hegnauer ◽  
Hendrik Buiteveld ◽  
...  
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Global Warming ◽  
Hydrological Model ◽  
Storage Capacity ◽  
Root Zone ◽  
Stationary System ◽  
Model Parameters ◽  
Hydrological Response ◽  
Historical Land Use

Abstract. To predict future hydrological behavior in a changing world, often use is made of models calibrated on past observations, disregarding that hydrological systems, hence model parameters, will change as well. Yet, ecosystems likely adjust their root-zone storage capacity, which is the key parameter of any hydrological system, in response to climate change. In addition, other species might become dominant, both under natural and anthropogenic influence. In this study, we propose a top-down approach, which directly uses projected climate data to estimate how vegetation adapts its root-zone storage capacity at the catchment scale in response to changes in magnitude and seasonality of hydro-climatic variables. Additionally, the Budyko characteristics of different dominant ecosystems in sub-catchments are used to simulate the hydrological behavior of potential future land-use change, in a space-for-time exchange. We hypothesize that changes in the predicted hydrological response as a result of 2 K global warming are more pronounced when explicitly considering changes in the sub-surface system properties induced by vegetation adaptation to changing environmental conditions. We test our hypothesis in the Meuse basin in four scenarios designed to predict the hydrological response to 2 K global warming in comparison to current-day conditions using a process-based hydrological model with (a) a stationary system, i.e. no changes in the root-zone storage capacity of vegetation and historical land use, (b) an adapted root-zone storage capacity in response to a changing climate but with historical land use, and (c, d) an adapted root-zone storage capacity considering two hypothetical changes in land use from coniferous plantations/agriculture towards broadleaved forest and vice-versa. We found that the larger root-zone storage capacities (+34 %) in response to a more pronounced seasonality with drier summers under 2 K global warming strongly alter seasonal patterns of the hydrological response, with an overall increase in mean annual evaporation (+4 %), a decrease in recharge (−6 %) and a decrease in streamflow (−7 %), compared to predictions with a stationary system. By integrating a time-dynamic representation of changing vegetation properties in hydrological models, we make a potential step towards more reliable hydrological predictions under change.

scholarly journals Hydrological model optimization using multi-gauge calibration (MGC) in a mountainous region

2020 ◽  
Author(s):  
Sead Ahmed Swalih ◽  
Ercan Kahya
Keyword(s):  
Climate Change ◽  
Model Calibration ◽  
Hydrological Model ◽  
Model Performance ◽  
Spatial Dimension ◽  
Model Parameters ◽  
Climate Projections ◽  
Predictive Capacity ◽  
Black Sea Region ◽  
The Impact

Abstract It is a challenge for hydrological models to capture complex processes in a basin with limited data when estimating model parameters. This study aims to contribute in this field by assessing the impact of incorporating spatial dimension on the improvement of model calibration. Hence, the main objective of this study was to evaluate the impact of multi-gauge calibration in hydrological model calibration for Ikizdere basin, Black Sea Region in Turkey. In addition, we have incorporated the climate change impact assessment for the study area. Four scenarios were tested for performance assessment of calibration: (1) using downstream flow data (DC), (2) using upstream data (UC), (3) using upstream and downstream data (Multi-Gauge Calibration – MGC), and (4) using upstream and then downstream data (UCDC). The results have shown that using individual gauges for calibration (1 and 2) improve the local predictive capacity of the model. MGC calibration significantly improved the model performance for the whole basin unlike 1 and 2. However, the local gauge calibrations statistical performance, compared to MGC outputs, was better for local areas. The UCDC yields the best model performance and much improved predictive capacity. Regarding the climate change, we did not observe an agreement amongst the future climate projections for the basin towards the end of the century.

scholarly journals Integrating Climate Change and Land Use Impacts to Explore Forest Conservation Policy

2017 ◽  
Author(s):  
Hyeyeong Choe ◽  
James H. Thorne
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Species Richness ◽  
Forest Policy ◽  
Forest Conversion ◽  
Climate Projections ◽  
Climate Change Scenarios ◽  
Land Use Impacts ◽  
Current Time ◽  
Future Policy

A scenario-based approach to the impacts of land use and climate change can help in identifying future policy directions. This study models the impacts of different land use and climate change scenarios on the forest ecosystems of South Korea to identify national-scale forest policy options. Climatically suitable forest areas for 1,031 climate vulnerable plant species were identified for current time and for 2050. We calculated change in species richness under four climate projections. We built forest conversion models and created four 2050 forest scenarios: (1) forest loss continues at current rates; (2) similar loss, but with conservation in areas with suitable future climates; (3) a reduction of loss by 50%; and (4) a combination of preservation and overall reduction of loss by 50%. We then crossed the forest conversion models with the climate-driven change in species richness, and categorized current forest areas into four classes to offer forest policy alternatives. By deploying the scenarios which preserve climatically suitable forests, the average species richness where forests converting to other land uses reduced significantly. We suggest conserving forests with suitable climates for biodiversity conservation and the establishment of forest plantations targeted to areas where species richness will decline based on our results.

scholarly journals Technical note: A new approach for comparing soil depth profiles using bootstrapped Loess regression (BLR)

2015 ◽  
Vol 12 (23) ◽  
pp. 19199-19211 ◽  
Author(s):  
A. M. Keith ◽  
P. Henrys ◽  
R. L. Rowe ◽  
N. P. McNamara
Keyword(s):  
Land Use ◽  
Soil Profile ◽  
Soil Depth ◽  
Technical Note ◽  
Model Parameters ◽  
Land Uses ◽  
Parametric Approach ◽  
Soil System ◽  
Depth Profiles ◽  
Non Parametric

Abstract. Understanding the consequences of different land uses for the soil system is important to better inform decisions based on sustainability. The ability to assess change in soil properties, throughout the soil profile, is a critical step in this process. We present an approach to examine differences in soil depth profiles between land uses using bootstrapped Loess regressions (BLR). This non-parametric approach is data-driven, unconstrained by distributional model parameters and provides the ability to determine significant effects of land use at specific locations down a soil profile. We demonstrate an example of the BLR approach using data from a study examining the impacts of bioenergy land use change on soil carbon (C). While this straightforward non-parametric approach may be most useful in comparing soil C or organic matter profiles between land uses, it can be applied to any soil property which has been measured at satisfactory resolution down the soil profile. It is hoped that further studies of land use and land management, based on new or existing data, can make use of this approach to examine differences in soil profiles.

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