Modeling the Impacts of Climate Change on Crop Yield and Irrigation in the Monocacy River Watershed, USA

Crop yield depends on multiple factors, including climate conditions, soil characteristics, and available water. The objective of this study was to evaluate the impact of projected temperature and precipitation changes on crop yields in the Monocacy River Watershed in the Mid-Atlantic United States based on climate change scenarios. The Soil and Water Assessment Tool (SWAT) was applied to simulate watershed hydrology and crop yield. To evaluate the effect of future climate projections, four global climate models (GCMs) and three representative concentration pathways (RCP 4.5, 6, and 8.5) were used in the SWAT model. According to all GCMs and RCPs, a warmer climate with a wetter Autumn and Spring and a drier late Summer season is anticipated by mid and late century in this region. To evaluate future management strategies, water budget and crop yields were assessed for two scenarios: current rainfed and adaptive irrigated conditions. Irrigation would improve corn yields during mid-century across all scenarios. However, prolonged irrigation would have a negative impact due to nutrients runoff on both corn and soybean yields compared to rainfed condition. Decision tree analysis indicated that corn and soybean yields are most influenced by soil moisture, temperature, and precipitation as well as the water management practice used (i.e., rainfed or irrigated). The computed values from the SWAT modeling can be used as guidelines for water resource managers in this watershed to plan for projected water shortages and manage crop yields based on projected climate change conditions.

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Climate change impacts on nutrient loads in the Yorkshire Ouse catchment (UK)

Hydrology and Earth System Sciences ◽

10.5194/hess-6-197-2002 ◽

2002 ◽

Vol 6 (2) ◽

pp. 197-209 ◽

Cited By ~ 70

Author(s):

F. Bouraoui ◽

L. Galbiati ◽

G. Bidoglio

Keyword(s):

Climate Change ◽

Assessment Tool ◽

Swat Model ◽

Climate Change Impacts ◽

Climate Change Scenarios ◽

Baseline Scenario ◽

Nutrient Loads ◽

Nitrogen And Phosphorus ◽

Temperature And Precipitation ◽

The Impact

Abstract. This study assessed the impact of potential climate change on the nutrient loads to surface and sub-surface waters from agricultural areas and was conducted using the Soil and Water Assessment Tool (SWAT) model. The study focused on a 3500 km2 catchment located in northern England, the Yorkshire Ouse. The SWAT model was calibrated and validated using sets of five years' measurements of nitrate and ortho-phosphorus concentrations and water flow. To increase the reliability of the hydrological model predictions, an uncertainty analysis was conducted by perturbing input parameters using a Monte-Carlo technique. The SWAT model was then run using a baseline scenario corresponding to an actual measured time series of daily temperature and precipitation, and six climate change scenarios. Because of the increase in temperature, all climate scenarios introduced an increase of actual evapotranspiration. Faster crop growth and an increased nutrient uptake resulted, as did an increase of annual losses of total nitrogen and phosphorus, however, with strong seasonal differences. Keywords: SWAT model, climate change, nutrient loads

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Estimating the potential impact of climate change on sunflower yield in the Konya province of Turkey

The Journal of Agricultural Science ◽

10.1017/s0021859621000101 ◽

2021 ◽

pp. 1-13

Author(s):

Hudaverdi Gurkan ◽

Vakhtang Shelia ◽

Nilgun Bayraktar ◽

Y. Ersoy Yildirim ◽

Nebi Yesilekin ◽

...

Keyword(s):

Climate Change ◽

Climate Models ◽

Global Climate ◽

Model Performance ◽

Global Climate Models ◽

Climate Projections ◽

Climate Change Scenarios ◽

Adaptation To Climate Change ◽

Impact Of Climate Change ◽

The Impact

Abstract The impact of climate change on agricultural productivity is difficult to assess. However, determining the possible effects of climate change is an absolute necessity for planning by decision-makers. The aim of the study was the evaluation of the CSM-CROPGRO-Sunflower model of DSSAT4.7 and the assessment of impact of climate change on sunflower yield under future climate projections. For this purpose, a 2-year sunflower field experiment was conducted under semi-arid conditions in the Konya province of Turkey. Rainfed and irrigated treatments were used for model analysis. For the assessment of impact of climate change, three global climate models and two representative concentration pathways, i.e. 4.5 and 8.5 were selected. The evaluation of the model showed that the model was able to simulate yield reasonably well, with normalized root mean square error of 1.3% for the irrigated treatment and 17.7% for the rainfed treatment, a d-index of 0.98 and a modelling efficiency of 0.93 for the overall model performance. For the climate change scenarios, the model predicted that yield will decrease in a range of 2.9–39.6% under rainfed conditions and will increase in a range of 7.4–38.5% under irrigated conditions. Results suggest that temperature increases due to climate change will cause a shortening of plant growth cycles. Projection results also confirmed that increasing temperatures due to climate change will cause an increase in sunflower water requirements in the future. Thus, the results reveal the necessity to apply adequate water management strategies for adaptation to climate change for sunflower production.

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Modelling Climate Change Impacts on the Seasonality of Water Resources in the Upper Ca River Watershed in Southeast Asia

The Scientific World JOURNAL ◽

10.1155/2014/279135 ◽

2014 ◽

Vol 2014 ◽

pp. 1-14 ◽

Cited By ~ 11

Author(s):

Pham Quy Giang ◽

Kosuke Toshiki ◽

Masahiro Sakata ◽

Shoichi Kunikane ◽

Tran Quoc Vinh

Keyword(s):

Climate Change ◽

Water Resources ◽

Southeast Asia ◽

Swat Model ◽

Dry Season ◽

Global Climate Models ◽

Wet Season ◽

River Watershed ◽

Ca River ◽

The Impact

The impact of climate change on the seasonality of water resources in the Upper Ca River Watershed in mainland Southeast Asia was assessed using downscaled global climate models coupled with the SWAT model. The results indicated that temperature and evapotranspiration will increase in all months of future years. The area could warm as much as 3.4°C in the 2090s, with an increase of annual evapotranspiration of up to 23% in the same period. We found an increase in the seasonality of precipitation (both an increase in the wet season and a decrease in the dry season). The greatest monthly increase of up to 29% and the greatest monthly decrease of up to 30% are expected in the 2090s. As a result, decreases in dry season discharge and increases in wet season discharge are expected, with a span of ±25% for the highest monthly changes in the 2090s. This is expected to exacerbate the problem of seasonally uneven distribution of water resources: a large volume of water in the wet season and a scarcity of water in the dry season, a pattern that indicates the possibility of more frequent floods in the wet season and droughts in the dry season.

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Impacts and uncertainties of climate change on streamflow of the Johor River Basin, Malaysia using a CMIP5 General Circulation Model ensemble

Journal of Water and Climate Change ◽

10.2166/wcc.2014.020 ◽

2014 ◽

Vol 5 (4) ◽

pp. 676-695 ◽

Cited By ~ 37

Author(s):

Mou Leong Tan ◽

Darren L. Ficklin ◽

Ab Latif Ibrahim ◽

Zulkifli Yusop

Keyword(s):

Climate Change ◽

River Basin ◽

General Circulation ◽

Swat Model ◽

Circulation Model ◽

Climate Projections ◽

Climate Change Scenarios ◽

Efficiency Coefficient ◽

Monthly Streamflow ◽

The Impact

The impact of climate change and uncertainty of climate projections from general circulation models (GCMs) from phase 5 of the Coupled Model Intercomparison Project (CMIP5) on streamflow in the Johor River Basin, Malaysia was assessed. Eighteen GCMs were evaluated, and the six that adequately simulated historical climate were selected for an ensemble of GCMs under three Representative Concentration Pathways (RCPs; 2.6 (low emissions), 4.5 (moderate emissions) and 8.5 (high emissions)) for three future time periods (2020s, 2050s and 2080s) as inputs into the Soil and Water Assessment Tool (SWAT) hydrological model. We also quantified the uncertainties associated with GCM structure, greenhouse gas concentration pathways (RCP 2.6, 4.5 and 8.5), and prescribed increases of global temperature (1–6 °C) through streamflow changes. The SWAT model simulated historical monthly streamflow well, with a Nash–Sutcliffe efficiency coefficient of 0.66 for calibration and 0.62 for validation. Under RCPs 2.6, 4.5, and 8.5, the results indicate that annual precipitation changes of 1.01 to 8.88% and annual temperature of 0.60–3.21 °C will lead to a projected annual streamflow ranging from 0.91 to 12.95% compared to the historical period. The study indicates multiple climate change scenarios are important for a robust hydrological impact assessment.

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Multimodel GCM-RCM Ensemble-Based Projections of Temperature and Precipitation over West Africa for the Early 21st Century

International Journal of Geophysics ◽

10.1155/2012/972896 ◽

2012 ◽

Vol 2012 ◽

pp. 1-19 ◽

Cited By ~ 92

Author(s):

I. Diallo ◽

M. B. Sylla ◽

F. Giorgi ◽

A. T. Gaye ◽

M. Camara

Keyword(s):

Climate Change ◽

West Africa ◽

Climate Models ◽

Global Climate ◽

Global Climate Models ◽

Future Climate ◽

Climate Projections ◽

Climate Change Scenarios ◽

Seasonal Temperature ◽

Temperature And Precipitation

Reliable climate change scenarios are critical for West Africa, whose economy relies mostly on agriculture and, in this regard, multimodel ensembles are believed to provide the most robust climate change information. Toward this end, we analyze and intercompare the performance of a set of four regional climate models (RCMs) driven by two global climate models (GCMs) (for a total of 4 different GCM-RCM pairs) in simulating present day and future climate over West Africa. The results show that the individual RCM members as well as their ensemble employing the same driving fields exhibit different biases and show mixed results in terms of outperforming the GCM simulation of seasonal temperature and precipitation, indicating a substantial sensitivity of RCMs to regional and local processes. These biases are reduced and GCM simulations improved upon by averaging all four RCM simulations, suggesting that multi-model RCM ensembles based on different driving GCMs help to compensate systematic errors from both the nested and the driving models. This confirms the importance of the multi-model approach for improving robustness of climate change projections. Illustrative examples of such ensemble reveal that the western Sahel undergoes substantial drying in future climate projections mostly due to a decrease in peak monsoon rainfall.

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Assessing the Sensitivity of Main Crop Yields to Climate Change Impacts in China

Atmosphere ◽

10.3390/atmos12020172 ◽

2021 ◽

Vol 12 (2) ◽

pp. 172

Author(s):

Yuan Xu ◽

Jieming Chou ◽

Fan Yang ◽

Mingyang Sun ◽

Weixing Zhao ◽

...

Keyword(s):

Climate Change ◽

Crop Yield ◽

Food Production ◽

Crop Yields ◽

Climatic Factors ◽

Climatic Data ◽

The South ◽

The North ◽

Output Elasticity ◽

The Impact

Quantitatively assessing the spatial divergence of the sensitivity of crop yield to climate change is of great significance for reducing the climate change risk to food production. We use socio-economic and climatic data from 1981 to 2015 to examine how climate variability led to variation in yield, as simulated by an economy–climate model (C-D-C). The sensitivity of crop yield to the impact of climate change refers to the change in yield caused by changing climatic factors under the condition of constant non-climatic factors. An ‘output elasticity of comprehensive climate factor (CCF)’ approach determines the sensitivity, using the yields per hectare for grain, rice, wheat and maize in China’s main grain-producing areas as a case study. The results show that the CCF has a negative trend at a rate of −0.84/(10a) in the North region, while a positive trend of 0.79/(10a) is observed for the South region. Climate change promotes the ensemble increase in yields, and the contribution of agricultural labor force and total mechanical power to yields are greater, indicating that the yield in major grain-producing areas mainly depends on labor resources and the level of mechanization. However, the sensitivities to climate change of different crop yields to climate change present obvious regional differences: the sensitivity to climate change of the yield per hectare for maize in the North region was stronger than that in the South region. Therefore, the increase in the yield per hectare for maize in the North region due to the positive impacts of climate change was greater than that in the South region. In contrast, the sensitivity to climate change of the yield per hectare for rice in the South region was stronger than that in the North region. Furthermore, the sensitivity to climate change of maize per hectare yield was stronger than that of rice and wheat in the North region, and that of rice was the highest of the three crop yields in the South region. Finally, the economy–climate sensitivity zones of different crops were determined by the output elasticity of the CCF to help adapt to climate change and prevent food production risks.

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Application of SWAT in Hydrological Simulation of Complex Mountainous River Basin (Part II: Climate Change Impact Assessment)

Water ◽

10.3390/w13111548 ◽

2021 ◽

Vol 13 (11) ◽

pp. 1548

Author(s):

Suresh Marahatta ◽

Deepak Aryal ◽

Laxmi Prasad Devkota ◽

Utsav Bhattarai ◽

Dibesh Shrestha

Keyword(s):

Climate Change ◽

River Basin ◽

Climate Models ◽

Assessment Tool ◽

Swat Model ◽

Global Climate Models ◽

Climate Data ◽

The Future ◽

The Impact ◽

Mountainous River

This study aims at analysing the impact of climate change (CC) on the river hydrology of a complex mountainous river basin—the Budhigandaki River Basin (BRB)—using the Soil and Water Assessment Tool (SWAT) hydrological model that was calibrated and validated in Part I of this research. A relatively new approach of selecting global climate models (GCMs) for each of the two selected RCPs, 4.5 (stabilization scenario) and 8.5 (high emission scenario), representing four extreme cases (warm-wet, cold-wet, warm-dry, and cold-dry conditions), was applied. Future climate data was bias corrected using a quantile mapping method. The bias-corrected GCM data were forced into the SWAT model one at a time to simulate the future flows of BRB for three 30-year time windows: Immediate Future (2021–2050), Mid Future (2046–2075), and Far Future (2070–2099). The projected flows were compared with the corresponding monthly, seasonal, annual, and fractional differences of extreme flows of the simulated baseline period (1983–2012). The results showed that future long-term average annual flows are expected to increase in all climatic conditions for both RCPs compared to the baseline. The range of predicted changes in future monthly, seasonal, and annual flows shows high uncertainty. The comparative frequency analysis of the annual one-day-maximum and -minimum flows shows increased high flows and decreased low flows in the future. These results imply the necessity for design modifications in hydraulic structures as well as the preference of storage over run-of-river water resources development projects in the study basin from the perspective of climate resilience.

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Urban Geometry Optimization to Mitigate Climate Change: Towards Energy-Efficient Buildings

Sustainability ◽

10.3390/su13010027 ◽

2020 ◽

Vol 13 (1) ◽

pp. 27

Author(s):

Hatem Mahmoud ◽

Ayman Ragab

Keyword(s):

Climate Change ◽

Heat Stress ◽

Thermal Efficiency ◽

Energy Demand ◽

Building Blocks ◽

Climate Projections ◽

Climate Change Scenarios ◽

Urban Geometry ◽

Outdoor Spaces ◽

The Impact

The density of building blocks and insufficient greenery in cities tend to contribute dramatically not only to increased heat stress in the built environment but also to higher energy demand for cooling. Urban planners should, therefore, be conscious of their responsibility to reduce energy usage of buildings along with improving outdoor thermal efficiency. This study examines the impact of numerous proposed urban geometry cases on the thermal efficiency of outer spaces as well as the energy consumption of adjacent buildings under various climate change scenarios as representative concentration pathways (RCP) 4.5 and 8.5 climate projections for New Aswan city in 2035. The investigation was performed at one of the most underutilized outdoor spaces on the new campus of Aswan University in New Aswan city. The potential reduction of heat stress was investigated so as to improve the thermal comfort of the investigated outdoor spaces, as well as energy savings based on the proposed strategies. Accordingly, the most appropriate scenario to be adopted to cope with the inevitable climate change was identified. The proposed scenarios were divided into four categories of parameters. In the first category, shelters partially (25–50% and 75%) covering the streets were used. The second category proposed dividing the space parallel or perpendicular to the existing buildings. The third category was a hybrid scenario of the first and second categories. In the fourth category, a green cover of grass was added. A coupling evaluation was applied utilizing ENVI-met v4.2 and Design-Builder v4.5 to measure and improve the thermal efficiency of the outdoor space and reduce the cooling energy. The results demonstrated that it is better to cover outdoor spaces with 50% of the overall area than transform outdoor spaces into canyons.

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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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Impact of climate change on streamflow and water quality in the upper Dong Nai river basin, Vietnam

La Houille Blanche ◽

10.1051/lhb/2018010 ◽

2018 ◽

pp. 70-79 ◽

Cited By ~ 1

Author(s):

Le Viet Thang ◽

Dao Nguyen Khoi ◽

Ho Long Phi

Keyword(s):

Climate Change ◽

Water Quality ◽

River Basin ◽

Sediment Load ◽

Swat Model ◽

Future Climate Change ◽

Climate Change Scenarios ◽

Nutrient Load ◽

Impact Of Climate Change ◽

The Impact

In this study, we investigated the impact of climate change on streamflow and water quality (TSS, T-N, and T-P loads) in the upper Dong Nai River Basin using the Soil and Water Assessment Tool (SWAT) hydrological model. The calibration and validation results indicated that the SWAT model is a reasonable tool for simulating streamflow and water quality for this basin. Based on the well-calibrated SWAT model, the responses of streamflow, sediment load, and nutrient load to climate change were simulated. Climate change scenarios (RCP 4.5 and RCP 8.5) were developed from five GCM simulations (CanESM2, CNRM-CM5, HadGEM2-AO, IPSL-CM5A-LR, and MPI-ESM-MR) using the delta change method. The results indicated that climate in the study area would become warmer and wetter in the future. Climate change leads to increases in streamflow, sediment load, T-N load, and T-P load. Besides that, the impacts of climate change would exacerbate serious problems related to water shortage in the dry season and soil erosion and degradation in the wet season. In addition, it is indicated that changes in sediment yield and nutrient load due to climate change are larger than the corresponding changes in streamflow.

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