Soil Water and Nitrogen Fluxes in Response to Climate Change in a Wheat–Maize Double Cropping System

The impact of soil nutrient depletion on crop production is a thoroughly researched issue; however, robust assessments on the impact of climate change on water and N fluxes in agroecosystem are lacking. The complexity of soil water and N fluxes in response to climate change under agroecosystems makes simulation-based approaches to this issue appealing. This study evaluated the responses of crop yield, soil water, and N fluxes of a wheat–maize rotation to two Representative Concentration Pathways climate scenarios (RCP4.5 and RCP8.5) at Tai’an, a representative site on the North China Plain (NCP). Results showed that the mean air temperature and accumulated precipitation for both winter wheat (Triticum aestivum L.) and summer maize (Zea mays L.) growing seasons changed in both magnitude and pattern under various climate scenarios. The temperature increases shortened the growth periods of these two crops by more than 13 days and decrease summer maize yields (P < 0.05). These results are illustrated by lower yield results associated with RCP4.5 (20.5%) and RCP8.5 (19.3%) climate scenarios, respectively. During the winter wheat growing season, water drainage examined in the climate scenarios was significantly higher (more than double) than the baseline, and there was no significant change to nitrate leaching and denitrification. In the summer maize growing season, with continuously rising temperatures, the ranking for evaporation was in the order baseline < RCP4.5 < RCP8.5, however, the opposite ranking applied for transpiration and evapotranspiration. The increase in water drainage was 1.4 times higher than the baseline, whereas the nitrate leaching in soil significantly decreased. Our simulation results provide an opportunity to improve the understanding of soil water and N fluxes in agroecosystems, which can lead to deficient or excess N under future climate conditions.

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Modelling soil water content variations under drought stress on soil column cropped with winter wheat

Journal of Hydrology and Hydromechanics ◽

10.2478/johh-2014-0036 ◽

2014 ◽

Vol 62 (4) ◽

pp. 269-276 ◽

Cited By ~ 1

Author(s):

Szilveszter Csorba ◽

Andrea Raveloson ◽

Eszter Tóth ◽

Viliam Nagy ◽

Csilla Farkas

Keyword(s):

Climate Change ◽

Drought Stress ◽

Winter Wheat ◽

Soil Water ◽

Soil Column ◽

Time Variability ◽

Efficiency Coefficient ◽

Soil Columns ◽

Swap Model ◽

The Impact

Abstract Mathematical models are effective tools for evaluating the impact of predicted climate change on agricultural production, but it is difficult to test their applicability to future weather conditions. We applied the SWAP model to assess its applicability to climate conditions, differing from those, for which the model was developed. We used a database obtained from a winter wheat drought stress experiment. Winter wheat was grown in six soil columns, three having optimal water supply (NS), while three were kept under drought-stressed conditions (S). The SWAP model was successfully calibrated against measured values of potential evapotranspiration (PET), potential evaporation (PE) and total amount of water (TSW) in the soil columns. The Nash-Sutcliffe model efficiency coefficient (N-S) for TWS for the stressed columns was 0.92. For the NS treatment, we applied temporally variable soil hydraulic properties because of soil consolidation caused by regular irrigation. This approach improved the N-S values for the wetting-drying cycle from -1.77 to 0.54. We concluded that the model could be used for assessing the effects of climate change on soil water regime. Our results indicate that soil water balance studies should put more focus on the time variability of structuredependent soil properties.

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Using a water budget model to anticipate the impact of climate change on groundwater recharge at the regional scale in cold and humid climates - example of southern Quebec (Canada)

10.5194/egusphere-egu21-6039 ◽

2021 ◽

Author(s):

Emmanuel Dubois ◽

Marie Larocque ◽

Sylvain Gagné

Keyword(s):

Climate Change ◽

Groundwater Recharge ◽

Water Budget ◽

Regional Scale ◽

Growing Season ◽

Annual Precipitation ◽

Climate Scenarios ◽

Budget Model ◽

Impact Of Climate Change ◽

The Impact

In cold and humid climates, rivers and superficial water bodies are often fed by groundwater with relatively constant inflows that are most visible during the summer (limited net precipitation) and the winter (limited runoff and infiltration). The harsh winter &#8211; short growing season succession could be drastically affected by climate change. Although water is abundant, extreme low flows are expected in the near future, most likely due to warmer summer temperatures, increased summer PET and possible lower summer precipitation. It is thus crucial to provide stakeholders with scenarios of future groundwater recharge (GWR) to anticipate the impacts of climate change on groundwater resources at the regional scale. This study aims to test the contributions of a superficial water budget model to estimate the impact of climate change on the regional GWR. The methodology is tested in a forested and agricultural region of southern Quebec, located between the St. Lawrence River and the Canada-USA border, and between the Quebec-Ontario border and Quebec City (36,000 km&#178;). Scenarios of GWR for the region are simulated with the HydroBudget model, performing a transient-state spatialized superficial water budget, and 12 climate scenarios (RCP 4.5 and 8.5, 1951-2100 period). The model was previously calibrated in the study area for the 1961-2017 period and provides spatially distributed runoff, actual evapotranspiration, and GWR fluxes at a 500 x 500 m resolution with a monthly time step. Climate scenarios show warming of the annual temperature from +2 to +5&#176;C and up to 20% increase of annual precipitation at the 2100 horizon compared to the 1981-2010 reference period. By the end of the century, the number of days above 0&#176;C could double between November and April, dividing by almost two the quantity of snow during winter. The clear trends of warming temperature leads to a clear actual evapotranspiration (AET) increase while the increasing variability in annual precipitation translates into more variable annual runoff and GWR. Although no annual GWR decrease is simulated, an increase of winter GWR (up to x2) is expected, linked to warmer winters and unfrozen soils, followed by a decrease for the rest of the year, linked to a longer growing season producing higher AET rates. Although simple in its simulation process, the use of a superficial water budget model simulating soil frost provides new insights into the possible future trends in the different hydrologic variables based on a robust understanding of past condition. Aside from providing scenarios of spatialized GWR (also runoff and AET) at the 2100 horizon for a large region, this study shows that a simple water budget model is an appropriate and affordable tool to provide stakeholders with useful data for water management in a changing climate.

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Characterizing Growing Season Length of Subtropical Coniferous Forests with a Phenological Model

Forests ◽

10.3390/f12010095 ◽

2021 ◽

Vol 12 (1) ◽

pp. 95

Author(s):

Yuan Gong ◽

Christina L. Staudhammer ◽

Susanne Wiesner ◽

Gregory Starr ◽

Yinlong Zhang

Keyword(s):

Climate Change ◽

Soil Water ◽

Prescribed Fire ◽

Water Availability ◽

Longleaf Pine ◽

Growing Season ◽

Soil Water Availability ◽

Future Climate Change ◽

Short Term ◽

Phenological Model

Understanding plant phenological change is of great concern in the context of global climate change. Phenological models can aid in understanding and predicting growing season changes and can be parameterized with gross primary production (GPP) estimated using the eddy covariance (EC) technique. This study used nine years of EC-derived GPP data from three mature subtropical longleaf pine forests in the southeastern United States with differing soil water holding capacity in combination with site-specific micrometeorological data to parameterize a photosynthesis-based phenological model. We evaluated how weather conditions and prescribed fire led to variation in the ecosystem phenological processes. The results suggest that soil water availability had an effect on phenology, and greater soil water availability was associated with a longer growing season (LOS). We also observed that prescribed fire, a common forest management activity in the region, had a limited impact on phenological processes. Dormant season fire had no significant effect on phenological processes by site, but we observed differences in the start of the growing season (SOS) between fire and non-fire years. Fire delayed SOS by 10 d ± 5 d (SE), and this effect was greater with higher soil water availability, extending SOS by 18 d on average. Fire was also associated with increased sensitivity of spring phenology to radiation and air temperature. We found that interannual climate change and periodic weather anomalies (flood, short-term drought, and long-term drought), controlled annual ecosystem phenological processes more than prescribed fire. When water availability increased following short-term summer drought, the growing season was extended. With future climate change, subtropical areas of the Southeastern US are expected to experience more frequent short-term droughts, which could shorten the region’s growing season and lead to a reduction in the longleaf pine ecosystem’s carbon sequestration capacity.

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Dynamics of soil organic carbon in the steppes of Russia and Kazakhstan under past and future climate and land use

Regional Environmental Change ◽

10.1007/s10113-021-01799-7 ◽

2021 ◽

Vol 21 (3) ◽

Author(s):

Susanne Rolinski ◽

Alexander V. Prishchepov ◽

Georg Guggenberger ◽

Norbert Bischoff ◽

Irina Kurganova ◽

...

Keyword(s):

Climate Change ◽

Land Use ◽

Organic Carbon ◽

Land Use Change ◽

Soil Organic Carbon ◽

Arable Land ◽

Future Climate ◽

Future Climate Change ◽

Climate Scenarios ◽

The Impact

AbstractChanges in land use and climate are the main drivers of change in soil organic matter contents. We investigated the impact of the largest policy-induced land conversion to arable land, the Virgin Lands Campaign (VLC), from 1954 to 1963, of the massive cropland abandonment after 1990 and of climate change on soil organic carbon (SOC) stocks in steppes of Russia and Kazakhstan. We simulated carbon budgets from the pre-VLC period (1900) until 2100 using a dynamic vegetation model to assess the impacts of observed land-use change as well as future climate and land-use change scenarios. The simulations suggest for the entire VLC region (266 million hectares) that the historic cropland expansion resulted in emissions of 1.6⋅ 1015 g (= 1.6 Pg) carbon between 1950 and 1965 compared to 0.6 Pg in a scenario without the expansion. From 1990 to 2100, climate change alone is projected to cause emissions of about 1.8 (± 1.1) Pg carbon. Hypothetical recultivation of the cropland that has been abandoned after the fall of the Soviet Union until 2050 may cause emissions of 3.5 (± 0.9) Pg carbon until 2100, whereas the abandonment of all cropland until 2050 would lead to sequestration of 1.8 (± 1.2) Pg carbon. For the climate scenarios based on SRES (Special Report on Emission Scenarios) emission pathways, SOC declined only moderately for constant land use but substantially with further cropland expansion. The variation of SOC in response to the climate scenarios was smaller than that in response to the land-use scenarios. This suggests that the effects of land-use change on SOC dynamics may become as relevant as those of future climate change in the Eurasian steppes.

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Impact of Climate Change on Potential Distribution of Chinese White Pine Beetle Dendroctonus armandi in China

Forests ◽

10.3390/f12050544 ◽

2021 ◽

Vol 12 (5) ◽

pp. 544

Author(s):

Hang Ning ◽

Ming Tang ◽

Hui Chen

Keyword(s):

Climate Change ◽

Potential Distribution ◽

Greenhouse Gas Emission ◽

Central China ◽

Qinling Mountains ◽

Climate Scenarios ◽

Impact Of Climate Change ◽

Precipitation Seasonality ◽

Suitable Area ◽

The Impact

Dendroctonus armandi (Coleoptera: Curculionidae: Scolytidae) is a bark beetle native to China and is the most destructive forest pest in the Pinus armandii woodlands of central China. Due to ongoing climate warming, D. armandi outbreaks have become more frequent and severe. Here, we used Maxent to model its current and future potential distribution in China. Minimum temperature of the coldest month and precipitation seasonality are the two major factors constraining the current distribution of D. armandi. Currently, the suitable area of D. armandi falls within the Qinling Mountains and Daba Mountains. The total suitable area is 15.83 × 104 km2. Under future climate scenarios, the total suitable area is projected to increase slightly, while remaining within the Qinling Mountains and Daba Mountains. Among the climate scenarios, the distribution expanded the most under the maximum greenhouse gas emission scenario (representative concentration pathway (RCP) 8.5). Under all assumptions, the highly suitable area is expected to increase over time; the increase will occur in southern Shaanxi, northwest Hubei, and northeast Sichuan Provinces. By the 2050s, the highly suitable area is projected to increase by 0.82 × 104 km2. By the 2050s, the suitable climatic niche for D. armandi will increase along the Qinling Mountains and Daba Mountains, posing a major challenge for forest managers. Our findings provide information that can be used to monitor D. armandi populations, host health, and the impact of climate change, shedding light on the effectiveness of management responses.

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The Impact of Climate Change on the Sugar Content of Grapes and the Sustainability of their Production in the Czech Republic

Sustainability ◽

10.3390/su13010222 ◽

2020 ◽

Vol 13 (1) ◽

pp. 222

Author(s):

Miroslava Navrátilová ◽

Markéta Beranová ◽

Lucie Severová ◽

Karel Šrédl ◽

Roman Svoboda ◽

...

Keyword(s):

Climate Change ◽

Czech Republic ◽

Sugar Content ◽

Growing Season ◽

Vegetation Period ◽

The Czech Republic ◽

Impact Of Climate Change ◽

Secondary Sources ◽

The Impact ◽

Growing Region

The aim of the presented article is to evaluate the impact of climate change on the sugar content of grapes in the Czech Republic during the period 2000–2019 through selected indicators on the basis of available secondary sources. Attention is focused on the developments in both the main wine-growing regions of Moravia and Bohemia. In the field of viticulture and wine-growing, the sugar content of grapes, as a basic parameter for the classification of wines, plays an important role. In the Czech Republic, the average sugar content of grapes has had a constantly growing trend. This trend is evident both in the wine-growing region of Bohemia and in the wine-growing region of Moravia. The impact of climate change, especially the gradual increase of average temperatures in the growing season, cannot be overlooked. It greatly affects, among other things, the sugar content of grapes. Calculations according to the Huglin Index and the Winkler Index were used to determine the relationship between climate and sugar content. These indexes summarize the course of temperatures during the entire vegetation period into a single numerical value. The results show that both indexes describe the effect of air temperature on sugar content in both wine regions of the Czech Republic in a statistically significant way. The Huglin Index shows a higher correlation rate. The Winkler Index proved to be less suitable for both areas. Alternatively, the Winkler Index calculated for a shorter growing season was tested, which showed a higher degree of correlation with sugar content, approaching the significance of the Huglin Index.

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Modeling the Impact of Climate Changes on Crop Yield: Irrigated vs. Non-Irrigated Zones in Mississippi

Remote Sensing ◽

10.3390/rs13122249 ◽

2021 ◽

Vol 13 (12) ◽

pp. 2249

Author(s):

Sadia Alam Shammi ◽

Qingmin Meng

Keyword(s):

Climate Change ◽

Crop Yield ◽

Crop Yields ◽

Negative Impact ◽

Positive Impact ◽

Information Criterion ◽

Growing Season ◽

Maximum Temperature ◽

Linear Regression Models ◽

The Impact

Climate change and its impact on agriculture are challenging issues regarding food production and food security. Many researchers have been trying to show the direct and indirect impacts of climate change on agriculture using different methods. In this study, we used linear regression models to assess the impact of climate on crop yield spatially and temporally by managing irrigated and non-irrigated crop fields. The climate data used in this study are Tmax (maximum temperature), Tmean (mean temperature), Tmin (minimum temperature), precipitation, and soybean annual yields, at county scale for Mississippi, USA, from 1980 to 2019. We fit a series of linear models that were evaluated based on statistical measurements of adjusted R-square, Akaike Information Criterion (AIC), and Bayesian Information Criterion (BIC). According to the statistical model evaluation, the 1980–1992 model Y[Tmax,Tmin,Precipitation]92i (BIC = 120.2) for irrigated zones and the 1993–2002 model Y[Tmax,Tmean,Precipitation]02ni (BIC = 1128.9) for non-irrigated zones showed the best fit for the 10-year period of climatic impacts on crop yields. These models showed about 2 to 7% significant negative impact of Tmax increase on the crop yield for irrigated and non-irrigated regions. Besides, the models for different agricultural districts also explained the changes of Tmax, Tmean, Tmin, and precipitation in the irrigated (adjusted R-square: 13–28%) and non-irrigated zones (adjusted R-square: 8–73%). About 2–10% negative impact of Tmax was estimated across different agricultural districts, whereas about −2 to +17% impacts of precipitation were observed for different districts. The modeling of 40-year periods of the whole state of Mississippi estimated a negative impact of Tmax (about 2.7 to 8.34%) but a positive impact of Tmean (+8.9%) on crop yield during the crop growing season, for both irrigated and non-irrigated regions. Overall, we assessed that crop yields were negatively affected (about 2–8%) by the increase of Tmax during the growing season, for both irrigated and non-irrigated zones. Both positive and negative impacts on crop yields were observed for the increases of Tmean, Tmin, and precipitation, respectively, for irrigated and non-irrigated zones. This study showed the pattern and extent of Tmax, Tmean, Tmin, and precipitation and their impacts on soybean yield at local and regional scales. The methods and the models proposed in this study could be helpful to quantify the climate change impacts on crop yields by considering irrigation conditions for different regions and periods.

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Analyzing competing land use policy objectives under climate change – a regional case study from Austria

10.5194/egusphere-egu21-8155 ◽

2021 ◽

Author(s):

Katrin Karner ◽

Hermine Mitter ◽

Erwin Schmid

Keyword(s):

Climate Change ◽

Land Use ◽

Organic Carbon ◽

Nitrate Leaching ◽

Climate Scenario ◽

Groundwater Extraction ◽

Climate Scenarios ◽

Abandoned Land ◽

Policy Objectives ◽

Net Benefits

In the semi-arid Seewinkel region in Austria, competing demands exist for land and water such as from agriculture, nature protection, tourism and settlements. In addition, water quality problems are prevalent due to nitrate leaching in groundwater in the region. Climate change likely will amplify existing resource demands and environmental impacts, imposing considerable challenges for adapting and regulating agriculture in the Seewinkel. Hence, compromises between competing policy objectives are needed. The aim of this presentation is to assess efficient land and water management strategies considering several economic and agro-ecological policy objectives in the Seewinkel region in context of climate scenarios. A multi-objective optimization experiment was performed with an integrated modelling framework to compute agro-economic-ecological Pareto frontiers. The frontiers combine levels of (i) net benefits from agricultural production, (ii) groundwater extraction for agricultural irrigation, (iii) nitrate leaching from agricultural production, and (iv) topsoil organic carbon stocks. 30 stochastic realizations of three climate scenarios are considered for a future period of 31 years: WET, SIMILAR and DRY, which mainly differ regarding annual precipitation volumes. Model results show that a 1% (20%) reduction of agricultural net benefits can lower groundwater extraction by 11-83% (61-100%) and nitrate leaching by 18-19% (49-53%) as well as increase topsoil organic carbon sequestration by 1% (5%) depending on the climate scenario. However, substantial changes in land use and management would be required. For instance, less groundwater extraction by 11-83% requires a 6-21% reduction of irrigated cropland, a 21-33% reduction of highly fertilized cropland, a 10-24% increase of grassland, and a 23-52% increase of abandoned land depending on the climate scenario. Less nitrate leaching by 18-19% (or higher topsoil organic carbon stocks by 1%) require that highly fertilized cropland decreases by 9-13% (4-7%), abandoned land increases by 5-9% (19-49%) and grassland either declines by 3% (14%) or increases by up to 5% (32%) depending on the climate scenario. In general, the share of grassland increases in the wetter climate scenario. Overall, the analysis reveals that especially groundwater extraction and nitrate leaching can be reduced substantially for fairly small reduction in agricultural net benefits in all climate scenarios. 50% of maximum modelled improvements of agro-ecological objectives can be already achieved at 1-15% reductions of agricultural net benefit depending on climate scenarios. Thus, respective land use policies would allow considerable improvements of the agro-ecological performance at relatively low costs. However, improving the agro-ecological performance beyond a particular level can quickly lead to high reductions of agricultural net benefits, as depicted by the non-linear form of the Pareto frontiers. This is mainly related to large declines of cropland and increases in grassland or abandoned land. Furthermore, the results indicate that water management policies are less costly than climate change mitigation policies, at least in the Seewinkel region.

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Spatial-temporal changes in river runoff and terrestrial ecosystem water retention under 1.5 °C and 2 °C warming scenarios across China

10.5194/esd-2017-96 ◽

2017 ◽

Author(s):

Ran Zhai ◽

Fulu Tao ◽

Zhihui Xu

Keyword(s):

Climate Change ◽

Interannual Variability ◽

River Runoff ◽

Water Retention ◽

Terrestrial Ecosystem ◽

Maximum Temperature ◽

Climate Scenarios ◽

Warming Scenario ◽

Basin Scale ◽

The Impact

Abstract. The Paris Agreement set a long-term temperature goal of holding the global average temperature increase to below 2.0 ℃ above pre-industrial levels, and pursuing efforts to limit this to 1.5 ℃, it is therefore important to understand the impacts of climate change under 1.5 ℃ and 2.0 ℃ warming scenarios for climate adaptation and mitigation. Here, climate scenarios by four Global Circulation Models (GCMs) for the baseline (2006–2015), 1.5 ℃ and 2.0 ℃ warming scenarios (2106–2115) were used to drive the validated Variable Infiltration Capacity (VIC) hydrological model to investigate the impacts of global warming on river runoff and Terrestrial Ecosystem Water Retention (TEWR) in China. The trends in annual mean temperature, precipitation, river runoff and TEWR were analysed at the grid and basin scale. Results showed that there were large uncertainties in climate scenarios from the different GCMs, which led to large uncertainties in the impact assessment. The differences among the four GCMs were larger than differences between the two warming scenarios. The interannual variability of river runoff increased notably in areas where it was projected to increase, and the interannual variability increased notably from 1.5 ℃ warming scenario to 2.0 ℃ warming scenario. By contrast, TEWR would remain relatively stable. Both extreme low and high river runoff would increase under the two warming scenarios in most areas in China, with high river runoff increasing more. And the risk of extreme river runoff events would be higher under 2.0 ℃ warming scenario than under 1.5 ℃ warming scenario in term of both extent and intensity. River runoff was significantly positively correlated to precipitation, while increase in maximum temperature would generally cause river runoff to decrease through increasing evapotranspiration. Likewise, precipitation also played a dominant role in affecting TEWR. Our findings highlight climate change mitigation and adaptation should be taken to reduce the risks of hydrological extreme events.

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