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 ◽  
...  

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.

2021 ◽  
Author(s):  
Laurène Bouaziz ◽  
Emma Aalbers ◽  
Albrecht Weerts ◽  
Mark Hegnauer ◽  
Hendrik Buiteveld ◽  
...  

<p>Models calibrated on the past are often used to predict future hydrological behavior in a changing world, disregarding that hydrological systems, hence model parameters, will change as well. Even if we are aware of the non-stationarity of hydrological systems, we are impeded by our limited knowledge on how to meaningfully implement this in hydrological models. Yet, ecosystems are likely to adapt in response to climate change and other species might become dominant, both under natural and anthropogenic influence. The root-zone storage capacity of ecosystems is an important hydrological parameter, which ecosystems can adjust in response to climatic change. 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. In order to make reliable estimates of hydrological behavior of future ecosystems, we exchange space-for-time, whereby the Budyko characteristics of different dominant ecosystems in sub-catchments are used to simulate the behavior of potential future land-use change. We hypothesize that predicted changes of the hydrological response as a result of 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°C global warming in comparison to current-day reference conditions using a process-based hydrological model with (1) a stationary system, i.e. no changes in the root-zone storage capacity of vegetation and historical land use, (2) an adapted root-zone storage capacity in response to a changing climate but with historical land use, and (3,4) 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 (+33%) in response to a more pronounced seasonality with drier summers under +2°C global warming strongly alter seasonal patterns of the hydrological response, with an overall increase in mean annual evaporation (+4%), and a decrease in recharge (-6%) and streamflow (-7%), compared to predictions with a stationary system. Through the integration of a time-dynamic representation of changing vegetation properties in hydrological models, we address the 19<sup>th</sup> Unsolved Problem in Hydrology (Blöschl et al., 2019) and move towards more reliable hydrological predictions under change.</p><p> </p><p>Blöschl, G., Bierkens, M. F. P., Chambel, A., Cudennec, C., Destouni, G., Fiori, A., et al. (2019). Twenty-three unsolved problems in hydrology (UPH) – a community perspective. <em>Hydrological Sciences Journal</em>, 64(10), 1141–1158. https://doi.org/10.1080/02626667.2019.1620507</p>


2021 ◽  
Vol 25 (9) ◽  
pp. 4887-4915
Author(s):  
Markus Hrachowitz ◽  
Michael Stockinger ◽  
Miriam Coenders-Gerrits ◽  
Ruud van der Ent ◽  
Heye Bogena ◽  
...  

Abstract. Deforestation can considerably affect transpiration dynamics and magnitudes at the catchment scale and thereby alter the partitioning between drainage and evaporative water fluxes released from terrestrial hydrological systems. However, it has so far remained problematic to directly link reductions in transpiration to changes in the physical properties of the system and to quantify these changes in system properties at the catchment scale. As a consequence, it is difficult to quantify the effect of deforestation on parameters of catchment-scale hydrological models. This in turn leads to substantial uncertainties in predictions of the hydrological response after deforestation but also to a poor understanding of how deforestation affects principal descriptors of catchment-scale transport, such as travel time distributions and young water fractions. The objectives of this study in the Wüstebach experimental catchment are therefore to provide a mechanistic explanation of why changes in the partitioning of water fluxes can be observed after deforestation and how this further affects the storage and release dynamics of water. More specifically, we test the hypotheses that (1) post-deforestation changes in water storage dynamics and partitioning of water fluxes are largely a direct consequence of a reduction of the catchment-scale effective vegetation-accessible water storage capacity in the unsaturated root zone (SU, max) after deforestation and that (2) the deforestation-induced reduction of SU, max affects the shape of travel time distributions and results in shifts towards higher fractions of young water in the stream. Simultaneously modelling streamflow and stable water isotope dynamics using meaningfully adjusted model parameters both for the pre- and post-deforestation periods, respectively, a hydrological model with an integrated tracer routine based on the concept of storage-age selection functions is used to track fluxes through the system and to estimate the effects of deforestation on catchment travel time distributions and young water fractions Fyw. It was found that deforestation led to a significant increase in streamflow accompanied by corresponding reductions of evaporative fluxes. This is reflected by an increase in the runoff ratio from CR=0.55 to 0.68 in the post-deforestation period despite similar climatic conditions. This reduction of evaporative fluxes could be linked to a reduction of the catchment-scale water storage volume in the unsaturated soil (SU, max) that is within the reach of active roots and thus accessible for vegetation transpiration from ∼258 mm in the pre-deforestation period to ∼101 mm in the post-deforestation period. The hydrological model, reflecting the changes in the parameter SU, max, indicated that in the post-deforestation period stream water was characterized by slightly yet statistically not significantly higher mean fractions of young water (Fyw∼0.13) than in the pre-deforestation period (Fyw∼0.12). In spite of these limited effects on the overall Fyw, changes were found for wet periods, during which post-deforestation fractions of young water increased to values Fyw∼0.37 for individual storms. Deforestation also caused a significantly increased sensitivity of young water fractions to discharge under wet conditions from dFyw/dQ=0.25 to 0.36. Overall, this study provides quantitative evidence that deforestation resulted in changes in vegetation-accessible storage volumes SU, max and that these changes are not only responsible for changes in the partitioning between drainage and evaporation and thus the fundamental hydrological response characteristics of the Wüstebach catchment, but also for changes in catchment-scale tracer circulation dynamics. In particular for wet conditions, deforestation caused higher proportions of younger water to reach the stream, implying faster routing of stable isotopes and plausibly also solutes through the sub-surface.


2014 ◽  
Vol 7 (5) ◽  
pp. 2359-2391 ◽  
Author(s):  
E. D. Keller ◽  
W. T. Baisden ◽  
L. Timar ◽  
B. Mullan ◽  
A. Clark

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.


2021 ◽  
Author(s):  
Xu Chen ◽  
Ruiguang Han ◽  
Yongjie Wang

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.


2014 ◽  
Vol 7 (3) ◽  
pp. 3307-3365
Author(s):  
E. D. Keller ◽  
W. T. Baisden ◽  
L. Timar ◽  
B. Mullan ◽  
A. Clark

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.


2019 ◽  
Vol 578 ◽  
pp. 124070 ◽  
Author(s):  
Soghra Andaryani ◽  
Vahid Nourani ◽  
Dennis Trolle ◽  
Maryam Dehghani ◽  
Abolfazl Mokhtari Asl

2012 ◽  
Vol 7 (5) ◽  
pp. 573-581 ◽  
Author(s):  
Subashisa Dutta ◽  
◽  
Shyamal Ghosh

Being the highest specific discharge river in the world, the Brahmaputra has a large floodplain area of 700 km in length in its middle reaches falling in the high flood vulnerability category. Floods generated in upland Himalayan catchments are mainly controlled by land use and land cover, storm characteristics, and vegetation dynamics. Floods propagate through a floodplain region consisting of wetlands, paddy agriculture, and wide braided river reaches with natural constraint points (nodals) that make the reaches more vulnerable to flood hazards. In this study, a macroscale distributed hydrological model was used to obtain the flood characteristics of the reaches. A hydrological model with spatially distributed input parameters and meteorological data was simulated at (1 km × 1 km) spatial grids to estimate flood hydrographs at the main river and itsmajor tributaries. Aftermodel validation, “best guess” land use change scenarios were used to estimate potential changes in flood characteristics. Results show that at the middle reaches of the Brahmaputra, peak discharge increases by a maximum of 9% for land use change scenarios. The same model with bias-corrected climatological data from a regional climate model (RCM) simulation (PRECIS) was used to obtain future changes in flood generation and its propagation through the basin in the projected climatological scenario. Changes in flood characteristics with reference to the baseline period show that the average duration of flood waves will increase from 15.2 days in the baseline period (1961-1990) to 19.3 days in the future (2071-2100). Peak discharge will increase by an average of 21% in the future in the projected climate change scenario. After statistics on changes of flood characteristics in the projected climate change scenario (2071-2100) were obtained, a 2-dimensional hydrodynamic model was used to obtain flood inundation and velocity distribution on the floodplain. Distribution of velocity and inundation depth was spatially analyzed to obtain flood hazard zones in the projected climate change scenario. Results show that spatial variation in flood hazard zones will be significantly altered in the projected climate change scenario compared to land use/land cover changes.


2017 ◽  
Vol 9 (3) ◽  
pp. 434-448 ◽  
Author(s):  
A. K. M. Saiful Islam ◽  
Supria Paul ◽  
Khaled Mohammed ◽  
Mutasim Billah ◽  
Md. Golam Rabbani Fahad ◽  
...  

Abstract The Ganges–Brahmaputra–Meghna river system carries the world's third-largest fresh water discharge and Brahmaputra alone carries about 67% of the total annual flow of Bangladesh. Climate change will be expected to alter the hydrological cycles and the flow regime of these basins. Assessment of the fresh water availability of the Brahmaputra Basin in the future under climate change condition is crucial for both society and the ecosystem. SWAT, a semi-distributed physically based hydrological model, has been applied to investigate hydrological response of the basin. However, it is a challenging task to calibrate and validate models over this ungauged and poor data basin. A model derived by using gridded rainfall data from the Tropical Rainfall Measuring Mission (TRMM) satellite and temperature data from reanalysis product ERA-Interim provides acceptable calibration and validation. Using the SWAT-CUP with SUFI-2 algorithm, sensitivity analysis of model parameters was examined. A calibrated model was derived using new climate change projection data from the multi-model ensemble CMIP5 Project over the South Asia CORDEX domain. The uncertainty of predicting monsoon flow is less than that of pre-monsoon flow. Most of the regional climate models (RCMs) show an increasing tendency of the discharge of Brahmaputra River at Bahadurabad station during monsoon, when flood usually occurs in Bangladesh.


2020 ◽  
Author(s):  
Nawa Raj Pradhan ◽  
Steven Brown ◽  
Ian Floyd

<p>Data acquisition and an efficient processing method for hydrological model initialization, such as soil moisture, and parameter value identification are critical for a physics based distributed watershed modelling of flood and flood related disasters such as sediment and debris flow. Site measurements can provide relatively accurate estimates of soil moisture, but such techniques are limited due to the need for a variety of measurement accessories, which are difficult to obtain to cover a large area sufficiently. Available satellite-based digital soil moisture data is at 9 kilometers to 50 kilometers in resolution which completely filters the soil moisture details at the hill slope scale. Moreover, available satellite-based digital soil moisture data represents only a few centimeters of the top soil column that informs nothing about the effective root-zone wetness. A recently developed soil moisture estimation method called SERVES (Soil moisture Estimation of Root zone through Vegetation index-based Evapotranspiration fraction and Soil properties) overcomes this limitation of satellite-based soil moisture data by estimating distributed root zone soil moisture at 30 meter resolution. In this study, a distributed watershed hydrological model of a sub-catchment of Reynolds Creek Experimental Watershed was developed with GSSHA (Gridded Surface Sub-surface Hydrological Analysis) Model. SERVES soil moisture estimated at 30 meter resolution was deployed in the watershed hydrological parameter value calibration and identification process. The 30 meter resolution SERVES soil moisture data was resampled to 4500 meter and 9000 meter resolutions and was separately employed in the calibrated hydrological model to determine the effect soil moisture resolution  has on the simulated outputs and the model parameters. It was found that the simulated discharge significantly decreased as the initial soil moisture resolution was coarsened. To compensate for this underestimated simulated discharge, the soil hydraulic conductivity value decreased logarithmically with respect to the decreased resolutions. This study will reduce parameter value identification uncertainty especially in flood and soil erosion modelling at multi scale watershed in a changing climate.</p>


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