Climate Change Influence On Ontario Corn Farms’ Income.

2021 ◽  
Author(s):  
Antoine Kornprobst ◽  
Matt Davison
Keyword(s):  
Climate Change ◽  
Farm Income ◽  
Change Scenario ◽  
Corn Yield ◽  
Time Step ◽  
Yield Data ◽  
Time Dynamic ◽  
Out Of Sample ◽  
The Impact ◽  
Annual Time

Abstract Our study quantifies the impact of climate change on the income of corn farms in Ontario, at the 2068 horizon, under several warming scenarios. It is articulated around a discrete- time dynamic model of corn farm income with an annual time-step, corresponding to one agricultural cycle from planting to harvest. At each period, we compute the income of a farm given the corn yield, which is highly dependent on weather variables: temperature and rainfall. We also provide a reproducible forecast of the yearly distribution of corn yield for the regions around ten cities in Ontario, located where most of the corn growing activity takes place in the province. The price of corn futures at harvest time is taken into account and we fit our model by using 49 years of county-level historical climate and corn yield data. We then conduct out-of-sample Monte-Carlo simulations in order to obtain the farm income forecasts under a given climate change scenario, from 0 ° C to + 4 ° C.

scholarly journals Comparing deep neural network and econometric approaches to predicting the impact of climate change on agricultural yield

2020 ◽  
Vol 23 (3) ◽  
pp. S59-S80
Author(s):  
Michael Keane ◽  
Timothy Neal
Keyword(s):  
Climate Change ◽  
Panel Data ◽  
Production Function ◽  
Fixed Effects ◽  
Data Models ◽  
Corn Yield ◽  
Panel Data Models ◽  
Yield Data ◽  
Impact Of Climate Change ◽  
The Impact

Summary Predicting the impact of climate change on crop yield is difficult, in part because the production function mapping weather to yield is high dimensional and nonlinear. We compare three approaches to predicting yields: (a) deep neural networks (DNNs), (b) traditional panel-data models, and (c) a new panel-data model that allows for unit and time fixed effects in both intercepts and slopes in the agricultural production function—made feasible by a new estimator called Mean Observation OLS (MO-OLS). Using U.S. county-level corn-yield data from 1950 to 2015, we show that both DNNs and MO-OLS models outperform traditional panel-data models for predicting yield, both in-sample and in a Monte Carlo cross-validation exercise. However, the MO-OLS model substantially outperforms both DNNs and traditional panel-data models in forecasting yield in a 2006–2015 holdout sample. We compare the predictions of all these models for climate change impacts on yields from 2016 to 2100.

scholarly journals Potential evaporation estimation through an unstressed surface-energy balance and its sensitivity to climate change

2013 ◽  
Vol 17 (11) ◽  
pp. 4625-4639 ◽  
Author(s):  
A. Barella-Ortiz ◽  
J. Polcher ◽  
A. Tuzet ◽  
K. Laval
Keyword(s):  
Climate Change ◽  
Energy Balance ◽  
Surface Energy ◽  
Surface Energy Balance ◽  
Aerodynamic Resistance ◽  
Neutral Stability ◽  
Potential Evaporation ◽  
Time Step ◽  
Humidity Gradient ◽  
The Impact

Abstract. Potential evaporation (ETP) is a basic input for many hydrological and agronomic models, as well as a key variable in most actual evaporation estimations. It has been approached through several diffusive and energy balance methods, out of which the Penman–Monteith equation is recommended as the standard one. In order to deal with the diffusive approach, ETP must be estimated at a sub-diurnal frequency, as currently done in land surface models (LSMs). This study presents an improved method, developed in the ORCHIDEE LSM, which consists of estimating ETP through an unstressed surface-energy balance (USEB method). The results confirm the quality of the estimation which is currently implemented in the model (Milly, 1992). The ETP underlying the reference evaporation proposed by the Food and Agriculture Organization, FAO, (computed at a daily time step) has also been analysed and compared. First, a comparison for a reference period under current climate conditions shows that USEB and FAO's ETP estimations differ, especially in arid areas. However, they produce similar values when the FAO's assumption of neutral stability conditions is relaxed, by replacing FAO's aerodynamic resistance by that of the model's. Furthermore, if the vapour pressure deficit (VPD) estimated for the FAO's equation, is substituted by ORCHIDEE's VPD or its humidity gradient, the agreement between the daily mean estimates of ETP is further improved. In a second step, ETP's sensitivity to climate change is assessed by comparing trends in these formulations for the 21st century. It is found that the USEB method shows a higher sensitivity than the FAO's. Both VPD and the model's humidity gradient, as well as the aerodynamic resistance have been identified as key parameters in governing ETP trends. Finally, the sensitivity study is extended to two empirical approximations based on net radiation and mass transfer (Priestley–Taylor and Rohwer, respectively). The sensitivity of these ETP estimates is compared to the one provided by USEB to test if simplified equations are able to reproduce the impact of climate change on ETP.

scholarly journals Integrated water resources management approach in mitigating the potential impacts of climate change on hydrology in Gurara reservoir catchment, Northwest Nigeria

2021 ◽  
Vol 384 ◽  
pp. 355-361
Author(s):  
Ifie-emi Francis Oseke ◽  
Geophery Kwame Anornu ◽  
Kwaku Amaning Adjei ◽  
Martin Obada Eduvie
Keyword(s):  
Climate Change ◽  
Water Resources ◽  
Water Resources Management ◽  
Climate Models ◽  
Linear Trend ◽  
Global Climate Models ◽  
Management Approach ◽  
Change Scenario ◽  
Resources Management ◽  
The Impact

Abstract. The strategies and actions in the management of African River Basins in a warming climate environment have been studied. Using the Gurara Reservoir Catchment in North-West Nigeria as a case study, summations were proposed using hypothetical climate scenarios considering the Global Climate Models prediction and linear trend of the data. Four (4) proposed scenarios of temperature increase (1 % and 2 %) coupled with a decrease in precipitation of (−5 % and −10 %) were combined and applied for the study area. The Water Evaluation and Planning Tool was used to model and evaluates the impact of the earth's rising temperature and declining rainfall on the hydrology and availability of water by investigating its resilience to climate change. Modelling results indicate a reduction in available water within the study area from 4.3 % to 3.5 % compared to the baseline with no climate change scenario, revealing the current water management strategy as not sustainable, uncoordinated, and resulting in overexploitation. The findings could assist in managing future water resources in the catchment by accentuating the need to put in place appropriate adaptation measures to foster resilience to climate change. Practically, it is pertinent to shape more effective policies and regulations within catchments for effective water resources management in reducing water shortage as well as achieving downstream water needs and power benefit in thefuture, while also allowing flexibility in the operation of a reservoir with the ultimate goal of adapting to climate change.

scholarly journals Impact of Farm Households’ Adaptations to Climate Change on Food Security: Evidence from Different Agro-ecologies of Pakistan

2016 ◽  
Vol 55 (4I-II) ◽  
pp. 561-588 ◽  
Author(s):  
Munir Ahmad Gattoo ◽  
Ghulam Mustafa ◽  
Muhammad Iqbal
Keyword(s):  
Climate Change ◽  
Food Security ◽  
Treatment Effects ◽  
New Technologies ◽  
Cropping Systems ◽  
Farm Households ◽  
Household Food Security ◽  
Farm Income ◽  
Household Food ◽  
The Impact

The study used data from 3298 food crop growers in Pakistan. Potential outcome treatment effects model was applied to evaluate the impact of adaptations on household food security. A household Food Security Index (FSI) was constructed applying Principle Component Analysis (PCA). Adaptation strategies employed by the farmers in response to climate change were categorised into four groups namely: changes in sowing time (C1); input intensification (C2); water and soil conservation (C3); and changes in varieties (C4). Out of 15 mutually exclusive combinations constructed for evaluation, only 7 combinations were considered for estimating the treatment effects models because of limited number of observations in other cases. Results of only two of the 7 are discussed in the paper, as the other 5 had very small number of adapters and the impact measures shown either insignificant results or had opposite signs. The first (C1234) combined all the four, while the second (C234) combined the last three strategies. The results suggest that the households which adapted to climate changes were statistically significantly more food secure as compared to those who did not adapt. The results further show that education of the male and female heads, livestock ownership, the structure of house—both bricked and having electricity facility, crops diversification, and non-farm income are among the factors, which raise the food security of farm households and their impacts are statistically significant. The variables which are significantly negatively associated with the food security levels include age of the head of household, food expenditure management, households having less than 12.5 acres of land— defined as marginal (cultivate 6.25 to 12.5 acres). Farmers of cotton-wheat, rice-wheat, and rain-fed cropping systems are found to be more food secure as compared to the farmers working in the mixed cropping systems where farm holdings are relatively small and high use of tube-well water adding to salinity of soils. It is crucial to invest in the development of agricultural technological packages, addressing issues of climate change relevant to different ecologies and farming systems; improve research-extension-farmer linkages; enhance farmers‘ access to new technologies; improve rural infrastructure; development of weather information system linking meteorological department, extension and farmers; and establishment of targeted food safety nets as well as farm subsidy programs for marginal farm households.

scholarly journals Estimating Sectoral Water Demand for Sindh Province of Pakistan

2020 ◽  
Vol 39 (2) ◽  
pp. 398-406
Author(s):  
Heman Das Lohano ◽  
Fateh Muhammad Marri
Keyword(s):  
Climate Change ◽  
Water Resources ◽  
Water Demand ◽  
Environmental Flows ◽  
Change Scenario ◽  
Total Water ◽  
Water Requirements ◽  
Sindh Province ◽  
The Impact ◽  
Total Water Demand

Water resources in Sindh province of Pakistan are under significant pressure due to increasing and conflicting water demand from municipalities for domestic users, agriculture and industries, and requirements of environmental flows. Population growth and climate change are likely to pose serious challenges to households and economic sectors that depend on water. This study estimates the present water demand from municipalities, agriculture and industries, and its future projections by the year 2050 in Sindh. The study also evaluates the impact of climate change on sectoral water demand and assesses the water requirements for the environmental flows. The results show that presently the total water demand for these sectors in Sindh is 44.06 Million Acre Feet (MAF). Agriculture is the largest consumer of water, accounting for 95.24 percent of the total water demand. Municipal water demand accounts for 2.61 percent while industrial water demand accounts for 1.88 percent. The demand for water in these sectors is expected to rise by 10 percent from 2018 to 2050. Moreover, depending on climate change scenario, the total water demand in these three sectors is likely to rise by 16 to 25 percent from 2018 to 2050. In additions, water requirements for the environmental flows have been indicated as 10 MAF in the National Water Accord of 1991. The findings of this study call for policy measures and strategies for management of water resources in Sindh.

scholarly journals Rapid Climate Adaption Assessment (RCAA) of water supply and sanitation services in two coastal urban poor communities in Accra, Ghana

2019 ◽  
Vol 11 (4) ◽  
pp. 1645-1660 ◽  
Author(s):  
Nikolaus Clemenz ◽  
Richard Boakye ◽  
Alison Parker
Keyword(s):  
Climate Change ◽  
Urban Poor ◽  
Service Providers ◽  
Solid Waste Management ◽  
Management Practice ◽  
Change Scenario ◽  
Water And Sanitation ◽  
Sanitation Services ◽  
The Impact ◽  
Poor Communities

Abstract This study assessed the impact of different hydrological scenarios on existing vulnerabilities of water and sanitation services in Chorkor and Shiabu, two coastal urban poor communities in Accra, Ghana. The hydrological scenarios were developed from the literature on climate change projections. This paper recommends adaptations for community members, service providers, and the municipality based on the impact assessment. Chorkor and Shiabu are vulnerable to an increase in rainfall because of the lack of adequate solid waste management and hydrological sound drains. Shiabu's topography and the indiscriminate sand mining along its beach make it vulnerable to an increase in sea level. Looking beyond Chorkor and Shiabu's community boundaries, the urban water utility which supplies water vendors in both communities may be severely impacted by a decrease in rainfall, which would lead to water scarcity and a shortage in hydroelectricity. Regardless of which climate change scenario emerges, many of the recommended adaptations are good water management practice, for example, increasing the number of household connections and reducing non-revenue water. Putting climate change high on the agenda has the potential to generate additional funding to help address Chorkor and Shiabu's water and sanitation problems, and climate-proof services for the future. However, the study method does not address the governance of these adaptations.

Impact of Climate Change on the Spatiotemporal Distribution of Stream Flow and Sediment Yield of Darbandikhan Watershed, Iraq

2020 ◽  
Vol 38 (2A) ◽  
pp. 265-276
Author(s):  
Mahmoud S. Al- Khafaji ◽  
Rana D. Al- Chalabi
Keyword(s):  
Climate Change ◽  
Sediment Yield ◽  
Stream Flow ◽  
Assessment Tool ◽  
Coefficient Of Determination ◽  
Base Period ◽  
Time Step ◽  
Impact Of Climate Change ◽  
Global Circulation Models ◽  
The Impact

The impact of climate change on stream flow and sediment yield in Darbandikhan Watershed is an important challenge facing the water resources in Diyala River, Iraq. This impact was investigated using five Global Circulation Models (GCM) based climate change projection models from the A1B scenario of medium emission. The Soil and Water Assessment Tool (SWAT) was used to compute the temporal and spatial distribution of streamflow and sediment yield of the study area for the period 1984 to 2050. The daily-observed flow recorded in Darbandikhan Dam for the period from 1984 to 2013 was used as a base period for future projection. The initial results of SWAT were calibrated and validated using SUFI-2 of the SWAT-CUP program in daily time step considering the values of the Nash-Sutcliffe Efficiency (NSE) coefficient of determination (R2) as a Dual objective function. Results of NSE and R2 during the calibration (validation) periods were equal to 0.61 and 0.62(0.53 and 0.68), respectively. In addition, the average future prediction for the five climate models indicated that the average yearly flow and sediment yield in the watershed would decrease by about 49% and 44%, respectively, until the year 2050 compared with these of the base period from 1984 to 2013. Moreover, spatial analysis shows that 89.6 % and 90 % of stream flow and sediment come from the Iranian part of Darbandikhan watershed while the remaining small percent comes from Iraq, respectively. However, the middle and southern parts of Darbandikhan Watershed contribute by most of the stream...

scholarly journals Assessing the Impact of Projected Climate Change on Zoo Visitation in Toronto (Canada)

2016 ◽  
Vol 8 (2) ◽  
pp. 30 ◽  
Author(s):  
Micah J. Hewer ◽  
William A. Gough
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Positive Impact ◽  
Global Climate ◽  
Global Climate Models ◽  
Change Scenario ◽  
Climate Change Scenarios ◽  
Intergovernmental Panel ◽  
Local Climate ◽  
The Impact

Weather and climate have been widely recognised as having an important influence on tourism and recreational activities. However, the nature of these relationships varies depending on the type, timing and location of these activities. Climate change is expected to have considerable and diverse impacts on recreation and tourism. Nonetheless, the potential impact of climate change on zoo visitation has yet to be assessed in a scientific manner. This case study begins by establishing the baseline conditions and statistical relationship between weather and zoo visitation in Toronto, Canada. Regression analysis, relying on historical weather and visitation data, measured at the daily time scale, formed the basis for this analysis. Climate change projections relied on output produced by Global Climate Models (GCMs) for the Intergovernmental Panel on Climate Change’s 2013 Fifth Assessment Report, ranked and selected using the herein defined Selective Ensemble Approach. This seasonal GCM output was then used to inform daily, local, climate change scenarios, generated using Statistical Down-Scaling Model Version 5.2. A series of seasonal models were then used to assess the impact of projected climate change on zoo visitation. While accounting for the negative effects of precipitation and extreme heat, the models suggested that annual visitation to the zoo will likely increase over the course of the 21st century due to projected climate change: from +8% in the 2020s to +18% by the 2080s, for the least change scenario; and from +8% in the 2020s to +34% in the 2080s, for the greatest change scenario. The majority of the positive impact of projected climate change on zoo visitation in Toronto will likely occur in the shoulder season (spring and fall); with only moderate increases in the off season (winter) and potentially negative impacts associated with the peak season (summer), especially if warming exceeds 3.5 °C.

scholarly journals Predicting the Impact of Climate Change on Thermal Comfort in A Building Category: The Case of Linear-type Social Housing Stock in Southern Spain

Energies ◽  
2019 ◽  
Vol 12 (12) ◽  
pp. 2238 ◽  
Author(s):  
Rocío Escandón ◽  
Rafael Suárez ◽  
Juan José Sendra ◽  
Fabrizio Ascione ◽  
Nicola Bianco ◽  
...  
Keyword(s):  
Climate Change ◽  
Thermal Comfort ◽  
Housing Stock ◽  
Climate Scenario ◽  
Southern Spain ◽  
Change Scenario ◽  
Linear Type ◽  
Average Percentage ◽  
The Impact ◽  
Do So

The Climate Change scenario projected by the IPCC for the year 2050 predicts noticeable increases in temperature. In severe summer climates, such as the Mediterranean area, this would have very negative effects on thermal comfort in the existing housing stock, given the current high percentage of dwellings which are obsolete in energy terms and house a population at serious risk of energy poverty. The main aim of this paper is to generate a predictive model in order to assess the impact of this future climate scenario on thermal comfort conditions in an entire building category. To do so, calibrated models representing linear-type social multi-family buildings, dating from the post-war period and located in southern Spain, will be simulated extensively using transient energy analyses performed by EnergyPlus. In addition, a sensitivity analysis will be performed to identify the most influential parameters on thermal discomfort. The main results predict a generalized deterioration in indoor thermal comfort conditions due to global warming, increasing the average percentage of discomfort hours during the summer by more than 35%. This characterization of the future thermal behaviour of the residential stock in southern Spain could be a trustworthy tool for decision-making in energy retrofitting projects which are so badly needed. To do so, further work is required on some limitations of this model so that different user profiles and typologies can be represented in detail and an economic assessment can be included.

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