General Circulation Model Projections Research Articles

Assessing the feasibility of sprinkler irrigation schemes and their adaptation to future climate change in groundwater over-exploitation regions

Promoting appropriate water-saving irrigation is an important pathway to alleviate groundwater overexploitation in irrigated agriculture. Whether an alternative irrigation method is feasible relies on quantitative assessments of its impacts on crop yield and hydrological cycle, especially in the groundwater overdraft area that faces a dilemma between water scarcity and food security. Using a groundwater-module-improved SWAT (Soil & Water Assessment Tool) model, five GCMs (General Circulation Models) projections of CMIP6 (Coupled Model Intercomparison Project 6), and a linear programming algorithm, sprinkler irrigation was simulated, evaluated, and optimized in a representative global groundwater mining location, the piedmont plain of the North China Plain. During the historical period (1993–2012), the results showed that, in general, sprinkler irrigation had advantages in benefiting crop transpiration of winter wheat and reducing percolation, hence improving water use efficiency with reference to traditional surface irrigation. Specifically, compared to traditional surface irrigation schemes, winter wheat yields increased by 12%− 14% with a 225 mm irrigation quota; they were stable with a 150 mm irrigation quota; but they decreased by 4% with a 75 mm irrigation quota. The shallow groundwater tables would decline at an average rate of 1.29 m/yr, 0.83 m/yr, and 0.35 m/yr, respectively, under sprinkler irrigation with 225 mm, 150 mm, and 75 mm irrigation quotas. Future climate changes (increased precipitation, air temperatures, and CO2 concentration) would bring effects of improving wheat yield by 6%− 7% and increasing groundwater vertical recharge by 58%− 122% in 2030–2049. The variations of predicted future shallow groundwater tables were − 0.37 m/yr, 0.01 m/yr, and 0.40 m/yr with the 225 mm, 150 mm, and 75 mm irrigation quotas, respectively, in the SSP2–4.5 scenario; and the corresponding results were − 0.45 m/yr, − 0.05 m/yr, and 0.34 m/yr in the SSP5–8.5 scenario. The optimization results showed that sprinkler irrigation could be implemented in approximately 50% of the study area to achieve shallow groundwater equilibrium and stable wheat production simultaneously in the near future. And the dominant sprinkler irrigation schedule after optimization was found to be scheme S3 (irrigation frequency for wheat was 5 times) with a limited irrigation quota of 150 mm. This study provides detailed data for planning sprinkler water-saving irrigation regimes and groundwater pumping strategies in China’s breadbasket, as well as a reference for global irrigated agriculture with over-drafted aquifers to balance groundwater conservation and grain production.

Future Projections of Low‐Level Atmospheric Circulation Patterns Over South Tropical South America: Impacts on Precipitation and Amazon Dry Season Length

AbstractThe last few decades have shown evidence of a lengthening dry season in southern Amazonia, which is associated with a delay in the onset of the South American Monsoon System (SAMS). Using a pattern recognition framework of atmospheric circulation patterns (CPs), previous studies have identified specific atmospheric situations related to the onset of the SAMS. Here, we analyze the future changes in the CPs that largely define the main hydro‐climatological states of Tropical South America. We evaluated the CP changes that occurred between two periods: historical (1970–2000) and future (2040–2070), using six General Circulation Models (GCMs) from the Coupled Model Intercomparison Project Phase 6. Future GCM projections show significant spatio‐temporal changes in the CPs associated with the dry season in southern Amazonia during the mid‐21st century. These changes are related to both a late onset of the SAMS and an early demise of the SAMS. Particularly, the CP methodology allowed for a better understanding of the behavior of the southern Amazon dry season under future conditions, showing an increase in the frequency of the CPs typically observed during the dry season. The occurrence of dry days in the Amazon basin during the austral winter of the mid‐21st century increases by 19.4% on average, with respect to the historical period. This methodology also identified a future increase in the frequency of dry CPs, both at the beginning of the dry‐to‐wet transition period (8%) and at the end of the wet‐to‐dry transition season (11%).

Assessment of impact of climate change on the streamflow of Idamalayar River Basin, Kerala

Abstract This study investigates the impacts of climate change on water availability in the Idamalayar basin, Kerala. Soil and Water Assessment Tool (SWAT), Hydrologic Engineering Centre – Hydrologic Modelling System (HEC-HMS), and bias-corrected climate change data were used to simulate future streamflows. The performances of SWAT and HEC-HMS were assessed using four statistical indices (R2, Nash–Sutcliffe efficiency, percentage bias, and RSR). SWAT slightly outperformed HEC-HMS. The CMIP6 general circulation models (GCMs) were selected using PROMETHEE-2. The variations in climate variables and streamflows were studied for three future periods, i.e., near-future (2031–2040), mid-future (2051–2060), and far-future (2071–2080) under three shared socio-economic pathway (SSP) scenarios (SSP126, SSP245, and SSP585). The projections of GCMs show different patterns in variation of precipitation. Generally, there is a slight increase in annual precipitation. However, there was a notable decline in peak in July. An additional peak was often seen in October. The maximum and minimum temperatures showed a decreasing trend. The average annual streamflow reduction under SSP126 was approximately 25.63, 27.92, and 26.24% in the near, mid, and far future, respectively. Under SSP245, the average decrease was 30.71, 16.06, and 19.06% for the near, mid and far future, respectively. For SSP585, there was 12.73% increase in the far-future period.

Climate change impact on the ecological status of rivers: The case of Albaida Valley (SE Spain)

Understanding the effects of environmental stressors (e.g., potential changes in climate and land use) on ecological status is essential for freshwater management. The ecological response of rivers to stressors can be evaluated by several physico-chemical, biological, and hydromorphological elements as well as computer tools. In this study, an ecohydrological model based on SWAT (Soil and Water Assessment Tool) is used to investigate climate change impact on the ecological status of Albaida Valley Rivers. The predictions of five General Circulation Models (GCMs) each with four Representative Concentration Pathways (RCPs) are employed as input to the model for simulating several chemical and biological quality indicators (nitrate, ammonium, total phosphorus, and the IBMWP (Iberian Biological Monitoring Working Party) index) in three future periods (Near Future: 2025–2049, Mid Future: 2050–2074, and Far Future: 2075–2099). Based on chemical and biological status predicted with the model, the ecological status is determined at 14 representative sites. As a result of increased temperatures and decreased precipitations from most of GCMs projections, the model predicts decreased river discharge, increased concentrations of nutrients, and decreased values of IBMWP for future compared to the baseline period (2005–2017). While most representative sites have poor ecological status (10 sites with poor ecological status and four sites with bad ecological status) in the baseline, our model projects bad ecological status for most representative sites (four sites with poor ecological status and 10 sites with bad ecological status) under most emission scenarios in the future. It should be noted that the bad ecological status is projected for all 14 sites under the most extreme scenario (i.e., RCP8.5) in the Far Future. Despite the different emission scenarios, and all possible changes in water temperature and annual precipitation, our findings emphasize the urgent need for scientifically informed decisions to manage and preserve freshwaters.

Agricultural conservation practices could help offset climate change impacts on cyanobacterial harmful algal blooms in Lake Erie

Harmful algal blooms (HABs) are a recurring problem in many temperate large lake and coastal marine ecosystems, caused mainly by anthropogenic eutrophication. Implementation of agricultural conservation practices (ACPs) offers a means to reduce non-point source nutrient runoff and mitigate HABs. However, the effectiveness of ACPs in a changing climate remains uncertain. We used an integrated biophysical modeling approach to predict how Lake Erie cyanobacterial HAB severity (bloom biomass) may change under several climate and ACP implementation scenarios, using western Lake Erie and its largely agricultural watershed as our study system. An ensemble of general circulation model projections was used to drive spatially explicit land use and hydrology models of the Maumee River watershed, the output of which informed a predictive model of Lake Erie HAB severity. Results show that, in the absence of changes in ACPs, the frequency of severe HABs is projected to increase during coming decades, owing to increased inputs of nutrients from the watershed. These anticipated increases are due to increased total precipitation and more frequent higher-magnitude rainfall events. While further implementation of ACPs appears capable of reducing severe HAB events, widespread implementation would be necessary to reduce HAB severity below current management targets. This study highlights how continued climate change will only exacerbate the need for land management practices that can reduce nutrient runoff in agriculturally dominated ecosystems, such as Lake Erie. It also shows how interdisciplinary, biophysical modeling approaches can help identify strategies to mitigate HABs in the face of anthropogenic stressors.

Effects of global climate change on the hydrological cycle and crop growth under heavily irrigated management – A comparison between CMIP5 and CMIP6

Quantifying the impact of global climate change on the water cycle and crop production is essential for water resource management and agricultural production planning. This study compared multiple GCM (General Circulation Model) projections of CMIP5 (Coupled Model Intercomparison Project 5) and CMIP6 and further used the selected GCMs to quantify the impact of future climate change on hydrology and crop production under intensive irrigation management in the North China Plain using an improved SWAT model (SWAT-MAD). Taylor’s skill score was used firstly to screen out six groups of GCMs with better simulation performance from 10 pairs of homologous GCMs of CMIP5 and CMIP6. The selected GCMs of CMIP5 and CMIP6 were further used to drive SWAT-MAD for a robust evaluation of climate change impacts. Results showed that during winter wheat growing season, average actual evapotranspiration (ETa) increased by 3%, 3%, 4%, and 5%, respectively, under 2041–2070 RCP4.5, 2041–2070 SSP2-4.5, 2041–2100 RCP4.5, and 2071–2100 SSP2-4.5 scenarios, compared to the historical period (1971–2000). During summer maize growing season, those changes in ETa were 4%, 2%, −0.2%, and −3%. Predicted future precipitation, air temperatures, and surface runoff could increase, while irrigation could decrease as precipitation increased. The dynamic patterns of leaf area index of winter wheat and summer maize indicated that there is a tendency for early emergence and maturity of both crops in the future, and the daily total biomass elevated with a corresponding increase in final yields. The highest increases in yields of winter wheat and summer maize were 18.9% and 16.7%. The findings not only contribute to enhancing the confidence of future projections using CMIP6 but also facilitate our understanding of the relative uncertainty of GCMs. This study provides technical and data support for pre-selections of GCMs and decision making in best management practices for groundwater conservation and agricultural production.

Climate change projection over Mainland Southeast Asia and the Lancang‐Mekong River basin based on a set of RegCM4 simulations

AbstractWe investigate the projected climate change over Mainland Southeast Asia (also known as the Indochina Peninsula) and the Lancang‐Mekong River basin, a region with complex topography and unique weather and climate systems, but limited availability of published high‐resolution regional climate model (RCM) studies. The study is based on an unprecedented ensemble of 21st century projections with the RegCM4 RCM driven by five different general circulation models (GCMs) at a grid spacing of 25 km under the representative concentration pathways RCP4.5 and RCP8.5. We focus on mean temperature and precipitation in the dry season November–March (NDJFM), the wet season May–September (MJJAS), and the whole year. Intercomparison between the RegCM4 simulations with the driving GCMs is provided to illustrate the added value of the RegCM4 experiments. RegCM4 reproduces greater and more realistic spatial detail of the present day temperature and precipitation distribution compared to the driving GCMs, but some biases are found, such as an overestimation of precipitation over high topography regions. The spatial pattern of biases shows some consistencies across the GCMs and, for NDJFM the RegCM4, although weak correlation is found between the GCM and nested RegCM4 biases. A generally lower warming is projected in the future by the RegCM4 in different seasons and the whole year. For precipitation, while prevailing increases are found in the GCM projections, large areas of decrease occur in the RegCM ones, in particular during the wet season, possibly due to the more detailed topographical representation. The change patterns of precipitation show consistencies across the GCMs and the RegCM4, especially in MJJAS. The projected changes of extreme indices indicate a general decrease/increase of extreme cold/warm events. Drought events are projected to be more frequent over the southwestern, while a general increase of heavy rain events prevails over most parts of the region.

Physically-based distributed modelling of the hydrology and soil erosion under changes in landuse and climate of a humid tropical river basin

The effects of landuse/landcover (LULC) and climate change on hydrology and soil erosion processes are of major concern, especially in the humid tropics. In this study, an evaluation of these changes is performed in a humid tropical catchment (Vamanapuram river basin, India) using a physically based distributed model, SHETRAN. The past landuse maps and climate data from six fine resolution NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) are used to force the SHETRAN model. A comparison of the change in the rate of soil erosion and hydrological responses during the future climate scenarios (near: 2021–2050 and far: 2071–2100) with respect to the historical period (1980–2005) is conducted.The isolated effects of landuse, climate variability and the combined effect caused change in streamflow (1.1%, 7.9%, 9.0% respectively) and sediment load (−10.4%, 1.7%, −10.5% respectively) in the past. An ensemble mean of general circulation model (GCM) projections showed that mean temperature and average annual precipitation under representative concentration pathway RCP 4.5 (8.5) scenarios for near and far futures increased from the historic period by 0.51 °C (1.6 °C), 0.6 °C (3.2 °C) and by 9% (6%), 15% (22.8%), respectively. Under RCP4.5(8.5), the average annual streamflow increased gradually from the near to far future, by 3.2% (−1.8%) and 13.6 % (22.1%) whereas, the projected sediment load a showed change of −21.05% (−26.63%) in near future while far future indicated change by −11% (4%). The SHETRAN model has been found to be effective in evaluating climate change impacts on hydrology and sediment yield and is useful for future river basin management.

How Do Regional Distributions of Daily Precipitation Change under Warming?

AbstractGlobal warming is changing the intensity distribution of daily precipitation, with an increased frequency of heavy precipitation and reduced frequency of light/moderate precipitation in general circulation model (GCM) projections. Projected future CMIP5 GCM changes in regional daily precipitation distribution can be described by a combination of two idealized modes: a frequency decrease mode, representing a reduction in the frequency of precipitation at all rain rates; and a frequency shift mode, where the distribution shifts toward heavier rain rates. A decrease in daily precipitation frequency and an increase in intensity are projected in most regions, but the magnitude of change shows large regional variations. The two modes generally capture the projected shift from light/moderate to heavy rain rates but do not recreate GCM changes at the very highest and lowest rain rates. We propose a simple framework for deep convective precipitation change based on the dry static energy (DSE) budget, which provides a physical explanation of these idealized modes in regions and seasons where deep convection dominates precipitation. One possibility is that a frequency decrease mode is driven by increased convective inhibition (CIN). In this DSE framework, increased moisture under warming could influence the shape of the precipitation intensity distribution, particularly at the highest rain rates, but does not govern the overall magnitude of the shift to heavier rain rates, which is not well described by the Clausius–Clapeyron relationship. Changes in daily regional precipitation are not free to respond only to local changes (in e.g., moisture) but are also constrained by the DSE budget, particularly by DSE transport associated with the large-scale circulation.

The Agricultural Sector and Climate Change in Mexico

Introduction: The agricultural sector is extremely vulnerable to climate change. Rising temperatures and changes in precipitation patterns would reduce crop production and lead to the proliferation of weeds, diseases and pests on crops. Changes in rainfall patterns increase the likelihood of short-term crop failure and long-term production reduction. Although some crops in certain regions of the world may benefit, the impacts of climate change are generally expected to be negative for agriculture. Likewise, the low availability of feed for livestock uses and the decrease in the availability of water will affect the productivity of milk and meat of the different breeds of cattle. Both low agricultural and livestock productivity threaten global food security.
 Objective: This research aims to highlight the impacts of climate change on the agricultural sector in Mexico. The present analysis uses regional modeling of climate variables under climate change conditions that impact crop growth and livestock development, using two scenarios to simulate future climate.
 Materials and Methods: the methodology is to present a set of regional projections of humidity, temperature, rainfall and Standardized Precipitation Evapotranspiration Indices (SPEI) for Mexico under the IPCC AR6 climate change scenarios, improving the projections of the Ocean-Atmospheric General Circulation Models and estimating the possible impacts of climate change on the agricultural sector of Mexico.
 Results and Discussion: Regional models for Mexico show temperature increases ranging from 0.5 to 5 °C, while the % change in rainfall will range from -20.3% to 13.5% depending on the scenario and analysis period. The low soil moisture (mm), the negative changes of Normalized Difference Vegetation Index (NDVI) and SPEI 12 show that the North, West and Bajío areas presented reductions in precipitation and increase in temperature that caused a severe deficit of soil moisture and water stress in the plants, considering these areas with scarce vegetation and presence of semi-permanent meteorological drought. Under these scenarios it is expected that practically the entire country will be subjected to moderate droughts (Center and South) to extremely strong (North) that will continue and sharpen between now and the end of the century. In Mexico, climate change will have various effects on crop yields, livestock reproduction and production of meat and its derivatives in all regions of the country in a differentiated way according to soil and climatic conditions. This will lead to additional price increases for major crops for both human and animal consumption. It will also cause not enough land suitable for cultivation and grazing; and availability of surface and groundwater demanded by the agricultural sector by the end of the 21st century.
 Conclusions: Finally, climate change will put Mexico's food security at risk during the present century.

Simulating the potential effects of elevated CO2 concentration and temperature coupled with storm intensification on crop yield, surface runoff, and soil loss based on 25 GCMs ensemble: A site-specific case study in Oklahoma

Proper simulation of storm intensification is critical in projecting crop yield, surface runoff, and soil loss under climate change conditions. We developed a total of 100 climate scenarios coupled with storm intensification, which were based on 25 downscaled GCMs (General Circulation Model) projections under RCP4.5 and RCP8.5 (Representative Concentration Pathways) for two time periods of 2021–2050 and 2051–2080. The climate files were applied to a modified WEPP (Water Erosion Prediction Project) model to estimate crop yield, runoff, and soil loss under 29 combinations of cropping and tillage systems. The results showed that future extreme storm events in the study area would significantly increase during 2021–2080 (P < 0.01). However, average monthly precipitation in summer would decrease by 12.5% in June and 10.8% in July, along with an annual precipitation decline of 2.6%, leading to a decrease in crop yield in this rainfed agricultural region. The amount of runoff (soil loss) from extreme storms would account for 45.9 (64.3%) of the total annual runoff (soil loss) when averaged across two time periods and two RCPs. The average annual runoff depth (soil loss amount) from crop rotation or double cropping systems would be 27.6 (78.1%) less than the corresponding values in a continuous monoculture cropping system. No-till and crop rotations with alfalfa are the best agricultural management alternatives to mitigate soil erosion rates under future climate change. The analysis of variance (ANOVA) indicated that the uncertainty contributions of GCMs and cropping and tillage systems reached 45.5% and 30.4% in annual surface runoff prediction (P < 0.001), while cropping and tillage systems (71.7%, P < 0.001) was the major uncertainty source in annual soil loss simulations. This study improved the prediction of crop yield, runoff, and soil loss from various cropping and tillage systems under climate change conditions by integrating storm intensification from multiple GCM ensembles.

The Mesoscale Response to Global Warming over the Pacific Northwest Evaluated Using a Regional Climate Model Ensemble

AbstractThis paper describes the downscaling of an ensemble of 12 general circulation models (GCMs) using the Weather Research and Forecasting (WRF) Model at 12-km grid spacing over the period 1970–2099, examining the mesoscale impacts of global warming as well as the uncertainties in its mesoscale expression. The RCP8.5 emissions scenario was used to drive both global and regional climate models. The regional climate modeling system reduced bias and improved realism for a historical period, in contrast to substantial errors for the GCM simulations driven by lack of resolution. The regional climate ensemble indicated several mesoscale responses to global warming that were not apparent in the global model simulations, such as enhanced continental interior warming during both winter and summer as well as increasing winter precipitation trends over the windward slopes of regional terrain, with declining trends to the lee of major barriers. During summer there is general drying, except to the east of the Cascades. The 1 April snowpack declines are large over the lower-to-middle slopes of regional terrain, with small snowpack increases over the lower elevations of the interior. Snow-albedo feedbacks are very different between GCM and RCM projections, with the GCMs producing large, unphysical areas of snowpack loss and enhanced warming. Daily average winds change little under global warming, but maximum easterly winds decline modestly, driven by a preferential sea level pressure decline over the continental interior. Although temperatures warm continuously over the domain after approximately 2010, with slight acceleration over time, occurrences of temperature extremes increase rapidly during the second half of the twenty-first century.Significance StatementThis paper provides a unique high-resolution view of projected climate change over the Pacific Northwest and does so using an ensemble of regional climate models, affording a look at the uncertainties in local impacts of global warming. The paper examines regional meteorological processes influenced by global warming and provides guidance for adaptation and preparation.

Low impact development practices mitigate urban flooding and non-point pollution under climate change

Climate change-induced extreme rainfall events exacerbate the failure in stormwater hydraulic and water quality management. As a promising alternative for stormwater management, the low impact development (LID) performance under the impact of climate change was analyzed in this study. The hydraulic and water quality models were integrated and the hydrological inputs were derived from downscaled general circulation model (GCM) projections. Results demonstrated that the LID practices in the given areas mitigated runoff volume, peak flow, and non-point pollution by 45–80%, 39–60%, and 31–82%, respectively. Scenario analysis showed that the LID hydraulic performance declined under all three future climate scenarios (RCP 2.6, RCP 4.5, and RCP 8.5), while the LID water quality performance fluctuated among different climate patterns. Uncertainty analysis suggested that the climate change caused wide-range uncertainties on LID performance, the uncertainty of LID water quality performance was larger than that of LID hydraulic performance. Spatial analysis indicated that the LID performance was spatially heterogeneous under climate change, and the heterogeneity was related to the land-cover distribution of the given area. In addition, sensitivity analysis suggested that the impact of climate change on the short-term performance of LID practices was stronger than that on the long-term performance. Accordingly, the methods and findings provided herein could assist sustainable urban water management by investigating the LID performance under climate change.

Modeling surface runoff and soil loss response to climate change under GCM ensembles and multiple cropping and tillage systems in Oklahoma

To develop effective conservation practices to respond to future climatic challenges, the effects of various cropping and tillage systems on surface runoff and soil loss need to be evaluated under extensive geographical conditions. This study used a total of 100 climate scenarios generated from 25 downscaled General Circulation Model (GCM) projections under two Representative Concentration Pathways (RCP4.5 and 8.5) during 2021–2050 and 2051–2080. Those 100 future scenarios were combined with 29 cropping and tillage systems to simulate surface runoff, soil erosion, and crop production response to climate change using the Water Erosion Prediction Project (WEPP) model. The results showed that average annual precipitation in central Oklahoma was projected to significantly decrease by 4–6% (p < 0.05) during the two time periods for both RCP scenarios. Mean annual temperatures were projected to significantly increase (p < 0.01) by 1.74 ℃ for RCP4.5 and 1.99 ℃ for RCP8.5 during 2021–2050, and 2.65 ℃ for RCP4.5 and 3.90 ℃ for RCP8.5 during 2051–2080. Annual runoff and soil loss averaged over the two RCPs and all crop types was projected to decrease by approximately 1% and 3%, respectively. Except for cotton, crop yields were predicted to decrease by 10.3%–18.3% during 2021–2080. Simulated annual runoff depth and soil loss separately followed the order of reduced tillage (RT) > delayed tillage (DT) > no-till (NT) > conventional tillage (CT) and RT > CT > DT > NT under future climate scenarios, respectively. If economically feasible, no-till and the crop-alfalfa rotation were the most effective soil conservation method on farmlands to combat projected future erosion due to changing precipitation and temperatures.

Managing flood risks in a changing climate

Managing flood risks in a changing climate

Evaluating the Applicability of a Quantile–Quantile Adjustment Approach for Downscaling Monthly GCM Projections to Site Scale over the Qinghai-Tibet Plateau

In the context of global climate change, the Qinghai-Tibetan plateau (QTP) has experienced unprecedented changes in its local climate. While general circulation models (GCM) are able to forecast global-scale future climate change trends, further work needs to be done to develop techniques to apply GCM-predicted trends at site scale to facilitate local ecohydrological response studies. Given the QTP’s unique altitude-controlled climate pattern, the applicability of the quantile–quantile (Q-Q) adjustment approach for this purpose remains largely unknown and warrants investigation. In this study, this approach was evaluated at 36 sites to ensure the results are representative of different climatic and surface conditions on the QTP. Considering the practical needs of QTP studies, the study aims to assess its capability for downscaling monthly GCM simulations of major variables onto the site scale, including precipitation, air temperature, wind speed, relative humidity, and air pressure, based on two GCMs. The calibrated projections at the sites were verified against the observations and compared with those from two commonly used adjustment methods—the quantile-mapping method and the delta method. The results show that the general trends of most variables considered are well adjusted at all sites, with a quantile pair of 25–75% for all the variables except precipitation where 10–90% is used. The calibrated results are generally close to the observed values, with the best performance in air pressure, followed by air temperature and relative humidity. The performance is relatively limited in adjusting wind speed and precipitation. The accuracies decline as the adjustment extends into the future; a wider adjustment window may help increase the performance for the variables subject to climate changes. It is found that the performance of the adjustment is generally independent of the locations and seasons, but is strongly determined by the quality of GCM simulations. The Q-Q adjustment works better for the meteorological variables with fewer fluctuations and daily extremes. Variables with more similarities in probability density functions between the observations and GCM simulations tend to perform better in adjustment. Generally, this approach outperforms the two peer methods with broader applicability and higher accuracies for most major variables.

Toward usable predictive climate information at decadal timescales

Toward usable predictive climate information at decadal timescales

Relating agriculture, energy, and water decisions to farm incomes and climate projections using two freeware programs, FEWCalc and DSSAT

CONTEXTThe larger scale perspective of Integrated Assessment (IA) and smaller scale perspective of Impacts, Adaptation, and Vulnerability (IAV) need to be bridged to design long-term solutions to agricultural problems that threaten agricultural production, rural economic viability, and global food supplies. FEWCalc (Food-Energy-Water Calculator) is a new freeware, agent-based model with the novel ability to project farm incomes based on crop selection, irrigation practices, groundwater availability, renewable energy investment, and historical and projected environmental conditions. FEWCalc is used to analyze the interrelated food, energy, water, and climate systems of Finney County, Kansas to evaluate consequences of choices currently available to farmers and resource managers. OBJECTIVEThis article aims to evaluate local farmer choices of crops and renewable energy investment in the face of water resource limitations and global climate change. Metrics of the analysis include agricultural and renewable-energy production, farm income, and water availability and quality. The intended audience includes farmers, resource managers, and scientists focusing on food, energy, and water systems. METHODSData derived from publicly available sources are used to support user-specified FEWCalc input values. DSSAT (Decision Support System for Agrotechnology Transfer) with added arid-region dynamics is used to obtain simulated crop production and irrigation water demand for FEWCalc. Here, FEWCalc is used to simulate agricultural and energy production and farm income based on continuation of recent ranges of crop prices, farm expenses, and crop insurance; continuation of recent renewable-energy economics and government incentives; one of four climate scenarios, including General Circulation Model projections for Representative Concentration Pathway 8.5; and groundwater-supported irrigation and its limitations. RESULTS AND CONCLUSIONSA 50-year (2018-2067) climate and groundwater availability projection process indicates possible trends of future crop yield, water utility, and farm income. The simulation during more wet years produces high crop production and slower depletion of groundwater, as expected. However, surprisingly, the simulations suggest that only the Drier Future scenario is commercially profitable, and this is because of reduced expenses for dryland farming. Although simulated income losses due to low crop production are ameliorated by the energy sector income and crop insurance, the simulation under climate change still produces the worst annual total income. SIGNIFICANCEFEWCalc addresses scientific, communication, and educational gaps between global- and local-scale FEW research communities and local stakeholders, affected by food, energy, water systems and their interactions by relating near-term choices to near- and long-term consequences. This analysis is needed to craft a more advantageous future.

A potential tipping point in the thermal regime of a warm monomictic reservoir under climate change using three-dimensional hydrodynamic modeling

ABSTRACT The response of the Maroon reservoir in southwest Iran is modeled to evaluate possible impacts of 21st century climate change. Projections of 3 CMIP5 General Circulation Models (GCMs) were investigated using 2 Representative Concentration Pathways (RCP4.5 and RCP8.5), which respectively represent low/medium and high greenhouse gas emission scenarios. The raw GCM projections are statistically bias-corrected to provide boundary conditions for the 3-dimensional Aquatic Ecosystem Model (AEM3D). A new overturn bias analysis method was developed to evaluate possible bias in the GCM predictors during the observational (historic) period and determined it to be negligible. The modeling results, quantified by the analysis of various limnological parameters (onset and length of mixing and stratification periods, hypolimnion and epilimnion thickness and temperature, Brunt-Väisälä frequency, and Schmidt stability) indicate for RCP4.5 a continuous reduction in winter mixing and complete suppression of mixing by the end of the 21st century, implying a switch from monomictic to weakly oligomictic behavior. Under RCP8.5, the behavior transition occurs abruptly in the late 2050s in the form of a tipping point, followed by intermittent oligomictic behavior and transition to permanent stratification (thermal meromixis) within a decade. The change in behavior occurs because the surface and mixing temperatures significantly increase due to climate warming, whereas the hypolimnion is less affected, partly because of milder warming of cold winter river inflows (underflow) and strengthening stratification. The climate change-induced tipping point for the thermal regime of Maroon reservoir might serve as an indicator of changes in other warm monomictic systems.

Climate change and cover crop effects on water use efficiency of a corn-soybean rotation system

Climate change led to increased temperature and variable rainfall, which may pose great threats to both agricultural productions and environmental impacts. In this study, we aim to explore how changing climate and its extremes in the 20th and 21st-century influence system water use efficiency (sWUE) of a corn-soybean cropping rotation in a humid sub-tropic environment, and how much can cover crops mitigate these impacts. Different from the traditional yield-focused water use efficiency (WUE), sWUE addresses both production and environmental quality goals by considering grain yields and all major system water losses (evapotranspiration, runoff, and drainage). A calibrated crop simulation model, Root Zone Water Quality Model version 2 (RZWQM2), was applied to simulate grain yields and all major system water losses. The model was forced by daily climate data from in situ observations during 1956–2015 and 10 downscaled and bias corrected General Circulation Model (GCMs) projections under the representative concentration pathways (RCP) 4.5 and 8.5 scenarios during 2020–2079. The results showed that, under the historical baseline and the future RCP4.5 and RCP8.5 scenarios, due to the growth of cover crops, the sWUE for corn were improved by 1.7%, 2.6% and 2.3%, respectively (p-value < 0.001), and for soybean by 0.7% (p = 0.06), 1.0% (p-value < 0.001) and 0.9% (p-value < 0.001). Soil evaporation, as the largest source of water loss from the cropping system, was significantly decreased by 1.7%, 2.6% and 2.3% during the corn growing season, and by 0.7%, 1.0% and 0.9% during the soybean growing season. The annual drainage was decreased by 38 mm, 53 mm and 67 mm, under the baseline, RCP4.5 and RCP8.5, respectively. With the incorporation of wheat cover crops, the correlations of temperature or precipitation extremes with grain yields and major water losses were mostly decreased, suggesting that growing cover crop is an effective means to mitigate the impact of climate extremes on sWUE of a corn-soybean cropping.