scholarly journals Predicting impacts of climate change on evapotranspiration and soil moisture for a site with subhumid climate

2019 ◽  
Vol 67 (4) ◽  
pp. 384-392
Author(s):  
András Herceg ◽  
Reinhard Nolz ◽  
Péter Kalicz ◽  
Zoltán Gribovszki
Keyword(s):  
Climate Change ◽  
Soil Moisture ◽  
Water Balance ◽  
Climate Models ◽  
Hydrological Cycle ◽  
Balance Model ◽  
Rooting Depth ◽  
Agricultural Field ◽  
Mean Values ◽  
Water Storage Capacity

Abstract The current and ongoing climate change over Europe can be characterized by statistically significant warming trend in all seasons. Warming has also an effect on the hydrological cycle through the precipitation intensity. Consequently, the supposed changes in the distribution and amount of precipitation with the continuously increasing temperature may induce a higher rate in water consumption of the plants, thus the adaptation of the plants to the climate change can be critical. The hydrological impact of climate change was studied based on typical environmental conditions of a specific agricultural area in Austria. For this purpose, (1) a monthly step, Thornthwaite-type water balance model was established and (2) the components of the water balance were projected for the 21st century, both (a) with a basic rooting depth condition (present state) and (b) with a (hypothetically) extended rooting depth (in order to evaluate potential adaption strategies of the plants to the warming). To achieve the main objectives, focus was set on calibrating and validating the model using local reference data. A key parameter of the applied model was the water storage capacity of the soil (SOILMAX), represented in terms of a maximum rooting depth. The latter was assessed and modified considering available data of evapotranspiration and soil physical properties. The adapted model was utilized for projections on the basis of four bias corrected Regional Climate Models. An extended rooting depth as a potential adaptation strategy for effects of climate change was also simulated by increasing SOILMAX. The basic simulation results indicated increasing evapotranspiration and soil moisture annual mean values, but decreasing minimum soil moisture for the 21st century. Seasonal examination, however, revealed that a decrease in soil moisture may occur in the growing season towards to the end of the 21st century. The simulations suggest that the vegetation of the chosen agricultural field may successfully adapt to the water scarcity by growing their roots to the possibly maximum.

scholarly journals A Monthly-Step Water Balance Model to Evaluate the Hydrological Effects of Climate Change on a Regional Scale for Irrigation Design

2016 ◽  
Vol 24 (4) ◽  
pp. 27-35
Author(s):  
A. Herceg ◽  
P. Kalicz ◽  
B. Kisfaludi ◽  
Z. Gribovszki
Keyword(s):  
Climate Change ◽  
Water Stress ◽  
Water Balance ◽  
Climate Model ◽  
Regional Scale ◽  
Stress Index ◽  
Balance Model ◽  
Rooting Depth ◽  
Model Parameters ◽  
Water Storage Capacity

AbstractCurrent and ongoing changes in the climate are typified by a rise in global temperatures. Climate change can have a dramatic impact on the water cycle. The aim of this paper was to develop a model based on Thornthwaite-type monthly water balance estimations. The main goals were to calibrate the model parameters using a remote sensing-based evapotranspiration dataset. The calibrated model was used for projection on the basis of four climate model datasets (remo, dmihirham5, smhirca.bcm, knmiracmo2). The four main projection periods were: 1980-2010, 2010-2040, 2040-2070, and 2070-2100. The advantage of this model is its robust structure. It can be applied if temperature and precipitation time series are available. The key parameter is the water storage capacity of the soil (SOILMAX), which can be calibrated using the actual evapotranspiration data available. If the physical properties of the soil are known, the maximal rooting depth is also projectable. The model can be primarily used at the catchment level or for areas without additional amounts of water from below. For testing the model, a mixed parcel of land that is used as a cornfield near Mosonmagyaróvár and a small, forest-covered catchment near Sopron were successfully used as the datasets. Furthermore, we determined the water stress with the calculation of the relative extractable water (REW), soil water deficit (SWD), and the water stress index (IS).

Stochastic soil moisture dynamic modelling: a case study in the Loess Plateau, China

2018 ◽  
Vol 109 (3-4) ◽  
pp. 437-444
Author(s):  
Cong WANG ◽  
Shuai WANG ◽  
Bojie FU ◽  
Lu ZHANG ◽  
Nan LU ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Water Balance ◽  
Loess Plateau ◽  
Hydrological Cycle ◽  
Dynamic Modelling ◽  
Vegetation Restoration ◽  
Balance Model ◽  
Rainfall Regime ◽  
The Loess Plateau ◽  
Dry Period

ABSTRACTSoil moisture is a key factor in the ecohydrological cycle in water-limited ecosystems, and it integrates the effects of climate, soil, and vegetation. The water balance and the hydrological cycle are significantly important for vegetation restoration in water-limited regions, and these dynamics are still poorly understood. In this study, the soil moisture and water balance were modelled with the stochastic soil water balance model in the Loess Plateau, China. This model was verified by monitoring soil moisture data of black locust plantations in the Yangjuangou catchment in the Loess Plateau. The influences of a rainfall regime change on soil moisture and water balance were also explored. Three meteorological stations were selected (Yulin, Yan'an, and Luochuan) along the precipitation gradient to detect the effects of rainfall spatial variability on the soil moisture and water balance. The results showed that soil moisture tended to be more frequent at low levels with decreasing precipitation, and the ratio of evapotranspiration under stress in response to rainfall also changed from 74.0% in Yulin to 52.3% in Luochuan. In addition, the effects of a temporal change in rainfall regime on soil moisture and water balance were explored at Yan'an. The soil moisture probability density function moved to high soil moisture in the wet period compared to the dry period of Yan'an, and the evapotranspiration under stress increased from 59.5% to 72% from the wet period to the dry period. The results of this study prove the applicability of the stochastic model in the Loess Plateau and reveal its potential for guiding the vegetation restoration in the next stage.

Assessing the options for the operational mapping of the soil moisture content in the European Alps

2021 ◽  
Author(s):  
Felix Greifeneder ◽  
Klaus Haslinger ◽  
Georg Seyerl ◽  
Claudia Notarnicola ◽  
Massimiliano Zappa ◽  
...  
Keyword(s):  
Climate Change ◽  
Soil Moisture ◽  
Temporal Dynamics ◽  
Hydrological Cycle ◽  
Balance Model ◽  
High Mountain ◽  
European Alps ◽  
Entire Area ◽  
Advantages And Disadvantages ◽  
Hourly Data

<p>Soil Moisture (SM) is one of the key observable variables of the hydrological cycle and therefore of high importance for many disciplines, from meteorology to agriculture. This contribution presents a comparison of different products for the mapping of SM. The aim was to identify the best available solution for the operational monitoring of SM as a drought indicator for the entire area of the European Alps, to be applied in the context of the Interreg Alpine Space project, the Alpine Drought Observatory.</p><p>The following datasets were considered: Soil Water Index (SWI) of the Copernicus Global Land Service [1]; ERA5 [2]; ERA5-Land [3]; UERRA MESCAN-SURFEX land-surface component [4]. All four datasets offer a different set of advantages and disadvantages related to their spatial resolution, update frequency and latency. As a reference, modelled SM time-series for 307 catchments in Switzerland were used [5]. Switzerland is well suited as a test case for the Alps, due to its different landscapes, from lowlands to high mountain.</p><p>The intercomparison was based on a correlation analysis of daily absolute SM values and the daily anomalies. Furthermore, the probability to detect certain events, such as persistent dry conditions, was evaluated for each of the SM datasets. First results showed that the temporal dynamics (both in terms of absolute values as well as anomalies) of the re-analysis datasets show a high correlation to the reference. A clear gradient, from the lowlands in the north to the high mountains in the south, with decreasing correlation is evident. The SWI data showed weak correlations to the temporal dynamics of the reference in general. Especially, during spring and the first part of the summer SM is significantly underestimated. This might be related to the influence of snowmelt, which is not taken into account in the two-layer water balance model used to model SM for deeper soil layers. Low coverage in the high mountain areas hampered a thorough comparison with the reference in these areas.</p><p>The results presented here are the foundation for selecting a suitable source for the operational mapping of SM for the Alpine Drought Observatory. The next steps will be to test the potential of MESCAN-SURFEX and ERA5-Land for the downscaling of ERA5 to take advantage of the low latency of ERA5 and the improved spatial detail of the other two datasets.  </p><p>Literature:</p><p>[1]  B. Bauer-marschallinger et al., “Sentinel-1 : Harnessing Assets and Overcoming Obstacles,” IEEE Trans. Geosci. Remote Sens., vol. 57, no. 1, pp. 520–539, 2019, doi: 10.1109/TGRS.2018.2858004.</p><p>[2]  H. Hersbach et al., “ERA5 hourly data on single levels from 1979 to present.” Copernicus Climate Change Service (C3S) Climate Data Store (CDS), 2018.</p><p>[3]  Copernicus Climate Change Service, “ERA5-Land hourly data from 2001 to present.” ECMWF, 2019, doi: 10.24381/CDS.E2161BAC.</p><p>[4]  E. Bazile, et al., “MESCAN-SURFEX Surface Analysis. Deliverable D2.8 of the UERRA Project,” 2017. Accessed: Jan. 11, 2020. [Online]. Available: http://www.uerra.eu/publications/deliverable-reports.html.</p><p>[5]  Brunner, et al.: Extremeness of recent drought events in    Switzerland: dependence on variable and return period choice, Nat. Hazards Earth Syst. Sci., 19, 2311–2323, https://doi.org/10.5194/nhess-19-2311-2019, 2019.</p>

Assessing the Hydrological Effect of Climate Change on Water Balance of a River Basin in Northern Greece

2018 ◽  
Vol 9 (4) ◽  
pp. 14-33
Author(s):  
Panagiota G. Koukouli ◽  
Pantazis E. Georgiou ◽  
Dimitrios K. Karpouzos
Keyword(s):  
Climate Change ◽  
Water Balance ◽  
River Basin ◽  
Climate Models ◽  
Baseline Period ◽  
Balance Model ◽  
Climate Change Scenarios ◽  
Northern Greece ◽  
Time Periods ◽  
Impacts Of Climate Change

In this work, the impacts of climate change on the water resources of the Olynthios River Basin in Northern Greece, were assessed. For this purpose, the climate change scenarios SRES and RCPs were used (SRES A1B, Α2 and RCP4.5, 8.5) - which were taken from two climate models, CGCM3.1/T63 and CanESM2, respectively - for two time periods (2031-2050 and 2081-2100) and for the baseline period (1981-2000). The downscaling was performed using the weather generator ClimGen. The monthly water balance of the Olynthios River Basin was estimated with the use of a conceptual water balance model. Results showed that the annual runoff of the river basin of Olynthios will decrease in response to climate change under all scenarios for both time periods. The results highlight the necessity for adequate adaptation strategies which could improve agricultural water management and reduce the impacts of climate change on agriculture.

Assessing the Hydrological Effect of Climate Change on Water Balance of a River Basin in Northern Greece

2022 ◽  
pp. 817-839
Author(s):  
Panagiota G. Koukouli ◽  
Pantazis E. Georgiou ◽  
Dimitrios K. Karpouzos
Keyword(s):  
Climate Change ◽  
Water Balance ◽  
River Basin ◽  
Climate Models ◽  
Baseline Period ◽  
Annual Runoff ◽  
Balance Model ◽  
Northern Greece ◽  
Time Periods ◽  
Impacts Of Climate Change

In this work, the impacts of climate change on the water resources of the Olynthios River Basin in Northern Greece, were assessed. For this purpose, the climate change scenarios SRES and RCPs were used (SRES A1B, Α2 and RCP4.5, 8.5) - which were taken from two climate models, CGCM3.1/T63 and CanESM2, respectively - for two time periods (2031-2050 and 2081-2100) and for the baseline period (1981-2000). The downscaling was performed using the weather generator ClimGen. The monthly water balance of the Olynthios River Basin was estimated with the use of a conceptual water balance model. Results showed that the annual runoff of the river basin of Olynthios will decrease in response to climate change under all scenarios for both time periods. The results highlight the necessity for adequate adaptation strategies which could improve agricultural water management and reduce the impacts of climate change on agriculture.

scholarly journals Testing an optimality-based model of rooting zone water storage capacity in temperate forests

2018 ◽  
Vol 22 (7) ◽  
pp. 4097-4124 ◽  
Author(s):  
Matthias J. R. Speich ◽  
Heike Lischke ◽  
Massimiliano Zappa
Keyword(s):  
Water Balance ◽  
Storage Capacity ◽  
Water Storage ◽  
Water Balance Model ◽  
Balance Model ◽  
Rooting Depth ◽  
Water Storage Capacity ◽  
Rooting Zone ◽  
Local Water ◽  
Zone Water

Abstract. Rooting zone water storage capacity Sr is a crucial parameter for modeling hydrology, ecosystem gas exchange and vegetation dynamics. Despite its importance, this parameter is still poorly constrained and subject to high uncertainty. We tested the analytical, optimality-based model of effective rooting depth proposed by Guswa (2008, 2010) with regard to its applicability for parameterizing Sr in temperate forests. The model assumes that plants dimension their rooting systems to maximize net carbon gain. Results from this model were compared against values obtained by calibrating a local water balance model against latent heat flux and soil moisture observations from 15 eddy covariance sites. Then, the effect of optimality-based Sr estimates on the performance of local water balance predictions was assessed during model validation. The agreement between calibrated and optimality-based Sr varied greatly across climates and forest types. At a majority of cold and temperate sites, the Sr estimates were similar for both methods, and the water balance model performed equally well when parameterized with calibrated and with optimality-based Sr. At spruce-dominated sites, optimality-based Sr were much larger than calibrated values. However, this did not affect the performance of the water balance model. On the other hand, at the Mediterranean sites considered in this study, optimality-based Sr were consistently much smaller than calibrated values. The same was the case at pine-dominated sites on sandy soils. Accordingly, performance of the water balance model was much worse at these sites when optimality-based Sr were used. This rooting depth parameterization might be used in dynamic (eco)hydrological models under cold and temperate conditions, either to estimate Sr without calibration or as a model component. This could greatly increase the reliability of transient climate-impact assessment studies. On the other hand, the results from this study do not warrant the application of this model to Mediterranean climates or on very coarse soils. While the cause of these mismatches cannot be determined with certainty, it is possible that trees under these conditions follow rooting strategies that differ from the carbon budget optimization assumed by the model.

scholarly journals Testing an optimality-based model of rooting zone water storage capacity in temperate forests

2017 ◽  
Author(s):  
Matthias J. R. Speich ◽  
Heike Lischke ◽  
Massimiliano Zappa
Keyword(s):  
Soil Moisture ◽  
Storage Capacity ◽  
Water Storage ◽  
Balance Model ◽  
Rooting Depth ◽  
Water Storage Capacity ◽  
Rooting Zone ◽  
Local Water ◽  
Zone Water ◽  
Good Agreement

Abstract. Rooting zone water storage capacity Sr is a crucial parameter in models of hydrology, ecosystem gas exchange and vegetation dynamics. Despite its importance, this parameter is still poorly constrained and subject to high uncertainty. We tested the analytical, optimality-based model of effective rooting depth proposed by Guswa (2010) with regard to its applicability for parameterizing Sr in temperate forests. The model assumes that plants dimension their rooting systems in order to maximize net carbon gain. Results from this model were compared against values obtained by calibrating a local water balance model against latent heat flux and soil moisture observations from 15 eddy covariance sites. To increase the applicability of the rooting depth model, we provide a numerical approximation of its underlying probabilistic soil moisture model. The calibration and validation of the local water balance model show that the concept of a single rooting zone storage capacity was appropriate at most temperate and cold sites, but not at Mediterranean sites and for very coarse soils. At a majority of sites, the estimates of Sr are generally in good agreement. However, mismatches were found in stands dominated by Norway spruce, especially at high elevations. These mismatches were attributed to the fact that the model does not consider rooting depth limitations due to oxygen stress and low soil temperature. Also, it is not clear whether the rooting behavior of pines on coarse soils is captured properly. Nevertheless, the overall good agreement suggests that this model may be useful for generating estimates of rooting zone storage capacity for both hydrological and ecological applications. Another potential use is the dynamic parameterization of the rooting zone in process-based models, which greatly increases the reliability of transient climate-impact assessment studies.

scholarly journals Assessment of the Impacts of Climate Change on Hydrological Characteristics of the Mbarali River Sub Catchment Using High Resolution Climate Simulations from CORDEX Regional Climate Models

2018 ◽  
Vol 10 (5) ◽  
pp. 61
Author(s):  
Edmund Mutayoba ◽  
Japhet J. Kashaigili ◽  
Frederick C. Kahimba ◽  
Winfred Mbungu ◽  
Nyemo A. Chilagane
Keyword(s):  
Climate Change ◽  
Water Balance ◽  
Climate Models ◽  
Regional Climate ◽  
Water Balance Components ◽  
Mean Values ◽  
Stream Flows ◽  
The Future ◽  
Rcp 8.5 ◽  
Impacts Of Climate Change

This study assesses the impacts of climate change on water resources over Mbarali River sub-catchment using high resolution climate simulations from the Coordinated Regional Climate Downscaling Experiment Regional Climate Models (CORDEX_RCMs). Daily rainfall, minimum and maximum temperatures for historical climate (1971-2000) and for the future climate projection (2011-2100) under two Representative Concentration Pathways RCP 8.5 and RCP 4.5 were used as input into the Soil and Water Assessment Tool (SWAT) hydrological model to simulate stream flows and water balance components for the Mbarali River sub-catchment. The impacts of climate change on hydrological conditions over Mbarali river catchment were assessed by comparing the mean values of stream flows and water balance components during the present (2011-2040), mid (2041-2070) and end (2071-2100) centuries with their respective mean values in the baseline (1971-2000) climate condition. The results of the study indicate that, in the future, under both RCP 4.5 and RCP 8.5 emission scenarios, the four main components that determine change in catchment water balance (rainfall, ground water recharge, evaporation and surface runoff) over Mbarali river catchment are projected to increase. While the stream flows are projected to decline in the future by 13.33% under RCP 4.5 and 13.67% under RCP 8.5 emission scenarios, it is important to note that simulated surface runoff under RCP8.5 emission scenario is higher than that which is obtained under the RCP4.5 emission scenario.

scholarly journals Regions of intensification of extreme snowfall under future warming

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Lennart Quante ◽  
Sven N. Willner ◽  
Robin Middelanis ◽  
Anders Levermann
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Observational Data ◽  
Climate Models ◽  
Hydrological Cycle ◽  
Global Climate ◽  
Global Climate Models ◽  
Average Intensity ◽  
High Latitudes ◽  
Future Warming

AbstractDue to climate change the frequency and character of precipitation are changing as the hydrological cycle intensifies. With regards to snowfall, global warming has two opposing influences; increasing humidity enables intense snowfall, whereas higher temperatures decrease the likelihood of snowfall. Here we show an intensification of extreme snowfall across large areas of the Northern Hemisphere under future warming. This is robust across an ensemble of global climate models when they are bias-corrected with observational data. While mean daily snowfall decreases, both the 99th and the 99.9th percentiles of daily snowfall increase in many regions in the next decades, especially for Northern America and Asia. Additionally, the average intensity of snowfall events exceeding these percentiles as experienced historically increases in many regions. This is likely to pose a challenge to municipalities in mid to high latitudes. Overall, extreme snowfall events are likely to become an increasingly important impact of climate change in the next decades, even if they will become rarer, but not necessarily less intense, in the second half of the century.

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