Carbon, nitrogen, and water response to climate and land use changes in Pennsylvania during the 20th and 21st centuries

Modeling the impact of climate change on soil organic carbon stock in upland soils in the 21st century in China

Using ORYZA2000 to model cold rice yield response to climate change in the Heilongjiang province, China

Climate warming has a rapid and far-reaching impact on forest fire management in the boreal forests of China. Regional climate model outputs and the Canadian Forest Fire Weather Index (FWI) System were used to analyze changes to fire danger and the fire season for future periods under IPCC Special Report on Emission Scenarios (SRES) A2 and B2, and the data will guide future fire management planning. We used regional climate in China (1961–1990) as our validation data, and the period (1991–2100) was modeled under SRES A2 and B2 through the weather simulated by the regional climate model system (PRECIS). Meteorological data and fire danger were interpolated to 1 km2 by using ANUSPLIN software. The average FWI value for future spring fire seasons under Scenarios A2 and B2 shows an increase over most of the region. Compared with the baseline, FWI averages of spring fire season will increase by −0.40, 0.26 and 1.32 under Scenario A2, and increase by 0.60, 1.54 and 2.56 under Scenario B2 in 2020s, 2050s and 2080s, respectively. FWI averages of autumn fire season also show an increase over most of the region. FWI values increase more for Scenario B2 than for Scenario A2 in the same periods, particularly during the 2050s and 2080s. Average future FWI values will increase under both scenarios for autumn fire season. The potential burned areas are expected to increase by 10% and 18% in spring for 2080s under Scenario A2 and B2, respectively. Fire season will be prolonged by 21 and 26 days under Scenarios A2 and B2 in 2080s respectively.

حوضه آجی­چای یکی از بزرگترین مناطق کشاورزی و مصرف آب در حوضه دریاچه ارومیه است که در سال­های اخیر به دلیل اثرات تغییر اقلیم و عوامل انسانی، کارکرد خود در تأمین حق­آبه دریاچه ارومیه را از دست داده است. از این­رو هدف مطالعه حاضر، بررسی اثرات سناریوهای اقلیمی و سناریوهای مدیریت منابع آب بر مقدار آب در دسترس، نیاز آبی گیاهان، الگوی کشت، عملکرد و سود کشاورزان در شهرستان سراب به عنوان یکی از سرشاخه­های اصلی آجی چای می­باشد. بدین منظور از مدل هیدرو- اقتصادی مبتنی بر ریسک بهره­ گرفته شد که در بخش اقتصادی از مدل برنامه­ریزی ریاضی درجه دوم توأم با ریسک و در بخش هیدرولوژیکی از مدل WEAP-MABIA استفاده گردید. داده­های مورد نیاز از تکمیل 210 پرسشنامه از کشاورزان در سال 1397 جمع­آوری گردید. برای تولید داده­های روزانه اقلیمی از مدل HadCM3 و ریزمقیاس­سازی LARS-WG تحت سناریوی­ها انتشار A2، B1 و A1B استفاده شد. نتایج نشان داد که تغییر اقلیم باعث کاهش سود و اشتغال بخش کشاورزی شده و الگوی کشت به سمت محصولات با نیاز آبی پایین تغییر خواهد یافت. اعمال سناریوی افزایش راندمان آبیاری علاوه بر استفاده مفید و موثرتر از آب تخصیصی، سود کشاورزان را نیز افزایش خواهد داد که نسبت به سناریو کاهش سهم آب کشاورزی وضعیت مطلوبتری را ارائه می­دهد. در مجموع نتایج این مطالعه بیانگر آن است که در صورت ثابت ماندن روش­های مدیریتی در آینده­ی نزدیک، عملکرد محصولات کاهش چشمگیری خواهد یافت. از این­رو بهینه­سازی روش­های مدیریتی و استفاده از ارقام با عملکرد بالاتر به­ عنوان راهکارهای مقابله با اثرات تغییر اقلیم توصیه می­شود.

How terrestrial ecosystems respond to future environmental change in the 21st century is critically important for understanding the feedbacks of terrestrial ecosystems to global climate change. The southeastern United States (SEUS) has been one of the major regions acting as a carbon sink over the past century; yet it is unclear how its terrestrial ecosystems will respond to global environmental change in the 21st century. Applying a process‐based ecosystem model (Dynamic Land Ecosystem Model, DLEM) in combination with three projected climate change scenarios (A1B, A2, and B1 from the IPCC report) and changes in atmospheric carbon dioxide, nitrogen deposition, and ozone pollution, we examined the potential changes of carbon storage and fluxes in the terrestrial ecosystems across the SEUS during 2000–2099. Simulation results indicate that SEUS's terrestrial ecosystems will likely continue to sequester carbon in the 21st century, resulting in an increase in total carbon density (i.e., litter, vegetation biomass and soil carbon) from 13.5 kg C/m2in the 2000s to 16.8 kg C/m2in the 2090s. The terrestrial gross primary production and net primary production will probably continuously increase, while the net carbon exchange (positive indicates sink and negative indicates source) will slightly decrease. The carbon sequestration is primarily attributed to elevated atmospheric carbon dioxide and nitrogen deposition. Forests, including both deciduous and evergreen, show the largest increase in carbon storage as compared with other biomes, while cropland carbon storage shows a small decrease. The sequestered carbon will be primarily stored in vegetation for deciduous forest and in soil for evergreen forest. The central and eastern SEUS will sequester more carbon, while the western portion of the SEUS will release carbon to the atmosphere. The combined effects of climate and atmospheric changes on carbon fluxes and storage vary among climate models and climate scenarios. The largest increase in carbon storage would occur under the A1B climate scenario simulated by the NCAR climate model. Generally, the A1B scenario would result in more carbon sequestration than A2 and B1 scenarios; and the projected climate condition by the NCAR model would result in more carbon sequestration than other climate models.

The purpose of this study is to investigate the future runoff into the Nong Han Lake under the effects of climate change. The hydrological model Soil and Water Assessment Tool (SWAT) has been selected for this study. The calibration and validation were performed by comparing the simulated and observed runoff from gauging station KH90 for the period 2001–2003 and 2004–2005, respectively. Future climate projections were generated by Providing Regional Climates for Impacts Studies (PRECIS) under the A2 and B2 scenarios. The SWAT model yielded good results in comparison to the baseline; moreover, the results of the PRECIS model showed that both precipitations and temperatures increased. Consequently, the amount of runoff calculated by SWAT under the A2 and B2 scenarios was higher than that for the baseline. In addition, the amount of runoff calculated considering the A2 scenario was higher than that considering the B2 scenario, due to higher average annual precipitations in the former case. The methodology and results of this study constitute key information for stakeholders, especially for the development of effective water management systems in the lake, such as designing a rule curve to cope with any future incidents.

Maximum entropy (Maxent) modeling was used to predict the potential climate habitat distribution of Chinese hybrid poplar (clone I-63, I-69 and I-72). Occurrence data were collected from literatures. The Maxent model performed better than random with an average cross-validated AUC value of 0.96. Under the three future climate scenarios (emission scenarios A1B, A2 and B1), the geographic distribution of suitable habitat would shift from southwest to northeast, the suitable habitat area of scenario A1B increased most compared to other two, the ranking of the loss habitat area was scenario B1 > scenario A2 > scenario A1B, and the gain habitat area was scenario A1B > scenario A2 > scenario B1. The results of this work could be used as scientific basis for adapting and mitigating Chinese hybrid poplar planting to a climate change.

Abstract. Climate change can cause significant modifications in hydrosedimentological processes. Climate projections indicate the occurrence of extreme events, in terms of precipitation, droughts, floods and temperature. By increasing temperatures and altering precipitation regimes, climate change is expected to affect sediment dynamics. Predictions of the effects of climate change on streamflow and sediment yield vary widely, depending on the geographical location and climate scenarios used. Mathematical modelling can be used to simulate the hydrosedimentological processes in watersheds and enable the simulation of climate change effects on sediment yield. This paper aims to simulate the impacts of climate change hydrosedimentological dynamics in the Apucaraninha River watershed (504 km²), southern Brazil, considering the climate change scenarios A2 (pessimistic about the emissions of greenhouse gases) and B2 (optimistic about the emissions of greenhouse gases), developed by the IPCC. The Soil and Water Assessment Tool (SWAT) was used to evaluate the impacts of climate projections on the sediment yield in the Apucaraninha River watershed. The model was calibrated and validated using daily streamflow and sediment data from 1987 to 2012. The model presented satisfactory fit to the observed data allowing the reproduction of the current hydrological conditions of the watershed. Based on the satisfactory results in calibration and validation, the climate scenarios A2 and B2 were inserted to simulate streamflow and sediment conditions for the period 2071–2100. The results for both scenarios indicate that simulations of both climate scenarios resulted in changes in hydrosedimentological dynamics in the Apucaraninha River watershed, mainly in terms of decrease in average sediment yield due to the reduction in precipitation amount and increase in evapotranspiration. Our results also indicate that every 1% change in precipitation has resulted in 2.8% change in soil erosion and 1.6% change in runoff under scenario A2, and 2.3% change in erosion and 1.1% in runoff under scenarios B2, thus suggesting that climate change tends to affect sediment yield more than streamflow, although seasonally both could be impacted in similar ways.

Impact assessments on climate change are essential for the evaluation and management of irrigation water in farming practices in semi-arid environments. This study was conducted to evaluate climate change impacts on water productivity of maize in farming practices in the Lower Chenab Canal (LCC) system. Two fields of maize were selected and monitored to calibrate and validate the model. A water productivity analysis was performed using the Soil–Water–Atmosphere–Plant (SWAP) model. Baseline climate data (1980–2010) for the study site were acquired from the weather observatory of the Pakistan Meteorological Department (PMD). Future climate change data were acquired from the Hadley Climate model version 3 (HadCM3). Statistical downscaling was performed using the Statistical Downscaling Model (SDSM) for the A2 and B2 scenarios of HadCM3. The water productivity assessment was performed for the midcentury (2040–2069) scenario. The maximum increase in the average maximum temperature (Tmax) and minimum temperature (Tmin) was found in the month of July under the A2 and B2 scenarios. The scenarios show a projected increase of 2.8 °C for Tmax and 3.2 °C for Tmin under A2 as well as 2.7 °C for Tmax and 3.2 °C for Tmin under B2 for the midcentury. Similarly, climate change scenarios showed that temperature is projected to decrease, with the average minimum and maximum temperatures of 7.4 and 6.4 °C under the A2 scenario and 7.7 and 6.8 °C under the B2 scenario in the middle of the century, respectively. However, the highest precipitation will decrease by 56 mm under the A2 and B2 scenarios in the middle of the century for the month of September. The input and output data of the SWAP model were processed in R programming for the easy working of the model. The negative impact of climate change was found under the A2 and B2 scenarios during the midcentury. The maximum decreases in Potential Water Productivity (WPET) and Actual Water Productivity (WPAI) from the baseline period to the midcentury scenario of 1.1 to 0.85 kgm−3 and 0.7 to 0.56 kgm−3 were found under the B2 scenario. Evaluation of irrigation practices directs the water managers in making suitable water management decisions for the improvement of water productivity in the changing climate.

Downscaling climate change scenarios in an urban land use change model

The goal of this study is to develop an agriculture planning model in order to sustain the future water use under the estimation of crop water requirement, water availability and future climate projection. For this purpose, the Citarum river basin which is located in West Java - Indonesia is selected as the study area. Two emission scenarios A2 and B2 were selected. For the crop water requirement estimation, the output of HadCM3 AOGCM is statistically downscale using SDSM and used as the input for WEAP model developed by SEI (Stockholm Environmental Institute). The reliability of water uses is assessed by comparing the irrigation water demand and the water allocation for the irrigation area. The water supply resources are assessed using the water planning tool. This study shows that temperature and precipitation over the study area are projected to increase in the future. The water availability was projected to increase under both A2 and B2 emission scenarios in the future. The irrigation water requirement is expected to decrease in the future under A2 and B2 scenarios. By comparing the irrigation water demand and water allocation for irrigation, the reliability of agriculture water use is expected to change in the period of 2050s and 2080s while the reliability will not change in 2020s. The reliability under A2 scenario is expected to be higher than B2 scenario. The combination of WEAP and SDSM is significance to use in assessing and allocating the water resources in the region.

Climate change would significantly affect the temporal pattern and amount of annual precipitation at the regional level, which in turn would affect the regional water resources and future water availability. The Peace Region is a critical region for northern British Columbia’s social, environmental, and economic development, due to its potential in various land use activities. This study investigated the impacts of future climate change induced precipitation on water resources under the A2 and B1 greenhouse gas emission scenarios for 2020–2040 in a study area along the main river of the Kiskatinaw River watershed in the Peace Region as a case study using the Gridded Surface Subsurface Hydrologic Analysis (GSSHA) modeling system. The simulation results showed that climate change induced precipitation changes significantly affect monthly, seasonal and annual stream flows. With respect to the mean annual stream flow of the reference period (2000–2011), the mean annual stream flow from 2020 to 2040 under the A2 and B1 scenarios is expected to increase by 15.5% and 12.1%, respectively, due to the increased precipitation (on average 5.5% in the A2 and 3.5% in the B1 scenarios) and temperature (on average 0.76 °C in the A2 and 0.57 °C in the B1 scenarios) predicted, with respect to that under the reference period. From the seasonal point of view, the mean seasonal stream flow during winter, spring, summer and fall from 2020 to 2040 under the A2 scenario is expected to increase by 10%, 16%, 11%, and 11%, respectively. On the other hand, under the B1 scenario these numbers are 6%, 15%, 6%, and 8%, respectively. Increased precipitation also resulted in increased groundwater discharge and surface runoff. The obtained results from this study will provide valuable information for the study area in the long-term period for seasonal and annual water extractions from the river and allocation to the stakeholders for future water supply, and help develop a regional water resources management plan for climate change induced precipitation changes.

The impact of land use and climate change on late Holocene and future suspended sediment yield of the Meuse catchment

A general circulation model (GCM) and hydrological model SWAT (Soil and Water Assessment Tool) under forcing from A1B, B1, and A2 emission scenarios by 2030 were used to assess the implications of climate change on water balance of the Gorganrood River Basin (GRB). The results of MPEH5C models and multi-scenarios indicated that monthly precipitation generally decreases while temperature increases in various parts of the basin with the magnitude of the changes in terms of different stations and scenarios. Accordingly, seasonal ET will decrease throughout the GRB over the 2020s in all seasons except in summer, where a slight increase is projected for A1B and A2 scenarios. At annual scale, average quick flow and average low flow under the B1, A1B, and A2 scenarios are projected to decrease by 7.3 to 12.0% from the historical levels. Over the ensembles of climate change scenarios, the simulations project average autumn total flow declines of ∼10% and an overall range of 6.9 to 13.2%. In summer, the components of flow at the studied basin are expected to increase under A2 and A1B scenarios but will slightly decrease under B1 scenario. The study result addresses a likelihood of inevitable future climate change.

Climate change is now affecting global agricul- ture and food production worldwide. Nonetheless the direct link between climate change and food security at the nation- al scale is poorly understood. Here we simulated the effect of climate change on food security in China using the CERES crop models and the IPCC SRES A2 and B2 sce- narios including CO2 fertilization effect. Models took into account population size, urbanization rate, cropland area, cropping intensity and technology development. Our results predict that food crop yield will increase +3-11 % under A2 scenario and +4 % under B2 scenario during 2030-2050, despite disparities among individual crops. As a conse- quence China will be able to achieve a production of 572 and 615 MT in 2030, then 635 and 646 MT in 2050 under A2 and B2 scenarios, respectively. In 2030 the food security index (FSI) will drop from +24 % in 2009 to −4.5 % and +10.2 % under A2 and B2 scenarios, respectively. In 2050, however, the FSI is predicted to increase to +7.1 % and +20.0 % under A2 and B2 scenarios, respectively, but this increase will be achieved only with the projected decrease of Chinese population. We conclude that 1) the proposed food security index is a simple yet powerful tool for food security analysis; (2) yield growth rate is a much better indicator of food security than yield per se; and (3) climate change only has a moderate positive effect on food security as compared to other factors such as cropland area, population growth, socio-economic pathway and technology development. Relevant policy options and research topics are suggested accordingly.