Integrated assessment of localized SSP-RCP narratives for climate change adaptation in coupled human-water systems

Modelling the combined impacts of climate change and socio-economic development on waterborne pathogen transport

Protection of our water resources is essential to provide future generations with safe drinking water, recreational opportunities, and reliable ecosystem services. Climate and land use changes exert pressure on the quality of our water resources. Additionally, societal development may generate both positive and negative impacts on future water quality. Thus, decisions made today will impact the water quality of tomorrow. In this paper, we address the issue of future microbial water quality by combining Representative Concentration Pathways and Shared Socio-economic Pathways with projections of societal development, either downscaled to a local level or assessed by local organisations. We use Lake Vomb in Sweden (providing approximately 330 000 persons with drinking water) to illustrate our novel approach of assessing the impact of climate change and societal development on future microbial water quality. The approach includes norovirus, Escherichia coli (as an indicator organism), and Cryptosporidium. Further, we combine hydrological and hydrodynamic fate and transport modelling to simulate future water quality in the tributaries and at the drinking water intake. Future simulations are compared to a baseline scenario representing the current situation. Results show that climate change will reduce future water quality. However, we can also see that societal development significantly impacts microbial water quality, potentially counteracting the increases in microbial concentrations induced by climate change. Therefore, drinking water supply management must adapt to both future climate and societal development.

Projecting LUCC dynamics and ecosystem services in an emerging urban agglomeration under SSP-RCP scenarios and their management implications

Improving our knowledge of future dynamics of ecosystem services (ESs) in the face of climate change and human activities provides a crucial foundation to navigate complex environmental challenges, which are essential to attaining sustainable development particularly in urban regions. However, an existing dearth persists in thoroughly forecasting the intricate interplay of trade-offs and synergies, as well as ecosystem services bundling under distinct future scenarios. This study adopts an integrated research framework to understand the spatiotemporal dynamics of ESs in the Changsha-Zhuzhou-Xiangtan Urban Agglomeration (CZTUA) under three Shared Socioeconomic Pathway and Representative Concentration Pathway (SSP-RCP) scenarios (i.e., SSP126, SSP245 and SSP585). Our future scenarios suggest that the core urban area of CZTUA is projected to expand at the cost of forests and croplands by 2050. Furthermore, human-induced urbanization, particularly the high-intensity LUCC along the Xiangjiang river, significantly impacts ESs, resulting in lower ESs values. The trade-off effects between ESs are primarily observed between WY (water yield) and other ESs. Ecosystem service bundles (ESB) previously dominated by WY have significantly transitioned to CS (carbon storage)-HQ (habitat quality) bundle, especially in the urban core of CZTUA, which serves as an early warning of potential challenges related to water resources. Our study utilizes the latest climate and land use change predictions to evaluate ecosystems in urban agglomerations, and adopts a layered zoning strategy based on ESs, which provides decision-makers with reproducible tools to explore ecosystem changes.

Climate change and urban sprawl: Unveiling the escalating flood risks in river deltas with a deep dive into the GBM river delta

River deltas, such as the Ganges-Brahmaputra-Meghna (GBM) delta, are highly vulnerable to flooding, exacerbated by intense human activities and rapid urban growth. This study explores the evolution of urban flood risks in the GBM delta under the combined impacts of climate change and urban expansion. Unlike traditional assessments that focus on a single flood source, we consider multiple sources-coastal, fluvial, and pluvial. Our findings indicate that future urban expansion will significantly increase flood exposure, with a substantial rise in flood risk from all sources by the end of this century. Climate change is the main driver of increased coastal flood risks, while urban growth primarily amplifies fluvial, and pluvial flood risks. This highlights the urgent need for adaptive urban planning strategies to mitigate future flooding and support sustainable urban development. The extreme high emissions future scenario (SSP5-8.5) shows the largest urban growth and consequent flood risk, emphasizing the necessity for preemptive measures to mitigate future urban flooding. Our study provides crucial insights into flood risk dynamics in delta environments, aiding policymakers and planners in developing resilience strategies against escalating flood threats.

Future land use simulation model-based landscape ecological risk prediction under the localized shared socioeconomic pathways in the Xiangjiang River Basin, China

Landscape ecological risk (LER) is an effective index to identify regional ecological risk and measure regional ecological security. The localized shared socioeconomic pathways (LSSPs) can provide multi-scenario parameters of social and economic development for LER research. The research of LER under LSSPs is of scientific significance and practical value in curbing the breeding and spread of LER risk areas. In this study, land-cover raster files from 2010 to 2020 were used as the foundational data. Future land use simulation (FLUS), regression, and Markov chain models were used to predict the land cover patterns under the five LSSP scenarios in the Xiangjiang River Basin (XJRB) in 2030. Thus, an evaluation model was established, and the LER of the watershed was evaluated. We found that the rate of land cover change (LCC) in the XJRB between 2010 and 2020 had a higher intensity (increasing at an average of 18.89% per decade) than that projected under the LSSPs for 2020-2030 (averaging an increase of 8.58% per decade). Among the growth rates of all land use types in the XJRB, that of urban land was the highest (33.3%). From 2010 to 2030, the LER in the XJRB was classified as lower risk (33.73%), lowest risk (33.11%), and moderate risk (24.13%) for each decade. Finally, the LER exhibited significant heterogeneity among different scenarios. Specifically, the percentages of regions characterized by the highest (9.77%) and higher LER (9.75%) were notably higher than those in the remaining scenarios. The higher-level risk area under the localized SSP1 demonstrated a clear spatial reduction compared to those of the other four scenarios. In addition, in order to facilitate the differential management and control of LER by relevant departments, risk zoning was carried out at the county level according to the prediction results of LER. And we got three types of risk management regions for the XJRB under the LSSPs.

A simulation and risk assessment framework for water-energy-environment nexus: A case study in the city cluster along the middle reach of the Yangtze River, China

In the Anthropocene, there is a strong interlinkage among water, energy, and the environment. The water-energy-environment nexus (WEEN) has been vigorously advocated as an emerging development paradigm and a global research agenda. Based on the nexus concept, a framework for the WEEN complex system simulation and risk assessment is developed. The three metropolitan areas of the city cluster along the middle reaches of the Yangtze River (CCMRYR) are taken as the objects. Regional policies are combined with generic shared socio-economic pathways (SSPs) to form a localized SSPs suitable for the research region. The dynamic simulation of the WEEN complex system and the risk analysis are carried out with the combination of system dynamics models and copula functions. Results show that: There are obvious differences in water utilization, energy consumption, air pollutant emissions, and water pollutant emissions among the three metropolitan areas. The issue of high carbon intensity in the Wuhan Metropolitan Coordinating Region needs to be emphasized and solved from the perspective of optimizing the industrial structure. Adhering to current development patterns, there will be successive peaks in water utilization, energy consumption, and carbon emissions in Wuhan, Dongting Lake, and Poyang Lake Metropolitan Coordinating Region by 2030, leading to high synergy risks at the systemic level, with maximum values of 0.84, 0.85, 0.62, respectively. A development path based on conservation priorities indicates that future policymaking needs to prioritize a resource-saving and pollution-control development pattern directed by technological upgrading against the backdrop of scarce natural resource endowments. The localized SSPs are a beneficial extension that enriches the narrative of regional-scale SSPs. The evolutionary trajectories and risk assessments of WEEN complex systems under different localized SSPs provide a sweeping insight into the consequences of policy decisions, thus enabling policymakers to appraise policy rationality and implement appropriate corrective measures.

Development of a behaviour pattern-based testing approach for coupled socioeconomic and environmental models

Understanding the interactions between human and environmental systems is key to sustainable environmental management. Dynamically Coupled Socioeconomic system dynamics models integrated with physically-based Environmental Models (DCSEMs) are promising tools to appropriately capture the non-linear relationships between complex socioeconomic and biophysical systems, thereby supporting sustainable environmental management. However, existing approaches for testing integrated models are commonly based on the point-to-point analysis of model outputs, which is not suitable for DCSEMs that are behaviour pattern oriented. Consequently, the lack of well-defined behaviour pattern-based approaches has limited the adaptability of DCSEMs. To address this gap, this study proposes a novel behaviour pattern-based model testing approach that includes global sensitivity analysis (GSA), auto-calibration algorithms, and evaluation to assess behaviour pattern similarities between model outputs and real-world trends. The proposed approach is demonstrated through a real-world case study, in which an existing DCSEM is calibrated and evaluated to simulate water table depth in the Rechna Doab region of Pakistan. Compared to the conventional numerical point approach, the proposed approach is better suited for DCSEMs, as it replicates observed system behaviour patterns (as opposed to observed point values) over time. Furthermore, the outcomes of the Theil inequality statistical analysis and parameter distribution analysis provide evidence that the suggested approach is effective in testing and improving the performance of the DCSEM by capturing the spatial heterogeneity within the study area. The proposed behaviour-pattern testing procedure is a useful approach for model testing in data-limited, spatially-distributed DCSEMs.

Multiscale ecological niche modeling exhibits varying climate change impacts on habitat suitability of Madrean Pine-Oak trees

Anthropogenic climate change and increasing greenhouse gas emissions are expected to globally impact the biological function, community structure, and spatial distribution of biodiversity. Many existing studies explore the effect of climate change on biodiversity, generally at a single spatial scale. This study explores the potential effects of climate change on the habitat suitability of seven tree species at two distinct spatial scales: the Coronado National Forest (CNF), a local management area, and the Sierra Madre Occidental (SMO), an ecoregional extent. Habitat suitability was determined by extrapolating Ecological Niche Models (ENMs) based on citizen-science tree occurrence records into future climatic conditions using projected 30-year normals for two anthropogenic emissions scenarios through the end of the century. These ENMs, examined at a spatial resolution of 1 km2, are constructed using a mean average ensemble of three commonly used machine learning algorithms. The results show that habitat suitability is expected to decrease for all seven tree species at varying degrees. Results also show that climate-forcing scenario choice appears to be far less important for understanding changes in species habitat suitability than the spatial scale of modeling extent. Additionally, we observed non-linear changes in tree species habitat suitability within the SMO and CNF dependent on forest community type, latitude, and elevational gradient. The paper concludes with a discussion of the necessary steps to verify the estimated alters of these tree species under climate change. Most importantly, provides a framework for characterizing habitat suitability across spatial scales.

Influences of Climate Change and Land Use Change on the Habitat Suitability of Bharal in the Sanjiangyuan District, China

One of the biggest dangers to the degradation of biodiversity worldwide is climate change. Its oscillations in the future could result in potential alterations to species populations and habitat structure. With Sanjiangyuan District as the study site, an uncrewed aerial vehicle (UAV) was utilized to investigate the number and location of the bharal (Pseudois nayaur). The Maximum Entropy model and the Minimum Cumulative Resistance model (MaxEnt-MCR) were coupled to simulate the distribution of wildlife. On this basis, the future geographical distribution of bharal under different climate scenarios was simulated, and the ecological corridor and habitat centroid of bharal were revealed. The results showed that the suitable area of the bharal habitat was 4669 km², which was mainly concentrated in the Maduo, Qumalai, and Gonghe counties. The potential distribution of the species under different future climate scenarios had a decreasing trend. Under the SSP-245 scenario, the habitat area of bharal in 2030 and 2050 decreased by 25.68 and 44.61% compared with the present situation and cumulatively decreased by 1199 and 2083 km², respectively. Under the SSP-585 scenario, the habitat area of bharal in 2030 and 2050 decreased by 27.5 and 48.44%, with a total reduction of 1284 and 2262 km², respectively. Furthermore, a complete loss of habitat was predicted in Gonghe County by 2050. In addition, it was observed that the landscape structure in Sanjiangyuan District would be more fragmented and complex. The continued climate change will seriously affect the habitat distribution of this species. Therefore, preventive measures, such as protecting habitat areas and establishing ecological corridors for bharal, should be implemented in the Sanjiangyuan District. Such measures should not focus solely on the potential degradation but should also be extended to include potential distribution areas for future migration.