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This paper looks at the potential implications of land use and climate change for replenishment of the five aquifers which lie beneath the Upper Guadiana catchment in central Spain. The impacts of scenarios for climate and land use change on groundwater recharge are explored using a physically based hydrological model. (Research is the downward flux of water from the base of the root zone, beyond which water is no longer available for evapotranspiration and forms part of the groundwater resource.) The model is integrated for a series of climate change scenarios spanning the range of predictions from general circulation models. Aquifer replenishment through recharge from the main four cover types is examined for each scenario and the implications for groundwater resources are examined. These climate scenarios are then coupled with a scenario for change in irrigated land use in the Guadiana derived from a cellular automata model based on historical change. The implications of coupled climate and land use change are discussed. The results indicate that current climatic variability has greater impacts on groundwater recharge than a number of extreme scenarios for climatic change. Although the impact of the land use change scenario is greater than that of the climate change scenarios, it is still significantly less than current vairability and represents a relatively small change at the catchment scale. This change is too small to significantly affect groundwater resources but may impact surface flows.

The objective of this paper is to describe an easily understandable integrated modelling framework for analysing the combined effects of changes in land‐use and climate on the leaching of phosphorus using regional IPCC‐based land‐use and climate scenarios. In addition, the paper reflects on the added value of a geospatial data‐based modelling approach from a river basin management perspective.

Regional land‐use scenarios were simulated for the whole official river basin planning unit of the Oulujoki‐Iijoki River Basin District using a land‐use simulation model. The nutrient leaching modelling on phosphorus was carried out in another raster‐based freeware for a smaller sub‐basin, Temmesjoki river basin.

Regional land use scenarios could be simulated taking into account the local conditions, such as the vicinity to water, and development options in agriculture on regional scale. The magnitude and leaching pattern of phosphorus in the future is related to the overall share of agricultural land on drainage basin level. The authors’ results also indicate that the local spatial structure of built‐up and agricultural areas may play a central role in nutrient leaching assessment. If the spatial structure is of importance, this may have further implications for the environmental planners working with river basin management.

This research takes a step further in bringing the global scenario framework to the local and practical level for various practical purposes in river basin management. The research provides an approach to spatially identify the possible impact of changes in land‐use and in climatic conditions on nutrient leaching.

The purpose of the paper is to present a scenario‐based approach to river basin planning, and demonstrate how land‐use planning can be utilised as a strong measure in meeting the climate change challenges with new precipitation patterns during the current century.

The current research takes a scenario‐based approach to river basin planning. A modelling framework is defined to assess the effects of active spatial planning to mitigate the negative consequences of climate change in river basin management. In total, three models are included in the framework: a land‐use model, a runoff model, and a flooding screening model.

The research has demonstrated the advantages of using models and scenarios to assess the effects of climate change in river basin management, and how active spatial planning – in the current example afforestation – can mitigate negative consequences of climate change.

The current research demonstrates how to combine models from different fields into one integrated model for impact assessment.

The developed methodology will assist river basin managers to assess the effects of river basin management plans.

The consequences of climate change are mainstream topics discussed by most citizens and results from the models can facilitate a qualified debate.

The paper analyses the feasibility of using active spatial planning to mitigate the negative consequences of climate change, such as flooding along rivers. This work is original, as no such analysis has been carried out before.

This paper aims to promote urban–rural synergy in carbon reduction and achieve the dual carbon goal, reconstruct the low-carbon urban–rural spatial pattern and explore planning strategies for carbon mitigation in urban agglomerations.

The authors propose the idea of land governance zoning based on low-carbon scenario simulation, using the Beijing–Tianjin–Hebei (BTH) urban agglomeration as the empirical research area. Specifically, the authors analyze its spatiotemporal evolution characteristics of carbon balance over the past two decades and simulate the land use pattern under the scenario of low-carbon emission in 2030. Furthermore, the authors create spatial zoning rules combined with land use transition characteristics to classify the urban agglomeration into carbon sink restoration zone, carbon sink protection zone, carbon control development zone and carbon transition agriculture zone and put forward corresponding targeted governance principals.

The study findings classify the BTH urban agglomeration into carbon sink restoration zone, carbon sink protection zone, carbon control development zone and carbon transition agriculture zone, which account for 28.1%, 17.2%, 20.1% and 34.6% of the total area, respectively. The carbon sink restoration zone and carbon sink protection zone are mainly distributed in the northern and western parts and Bohai Rim region. The carbon transition agriculture zone and carbon control development zone are mainly distributed in the southeastern plain and Zhangjiakou.

The authors suggest restoring and rebuilding ecosystems mainly in the northwest and east parts to increase the number of carbon sinks and the stability of the ecosystem. Besides, measures should be taken to promote collaborative emission reduction work between cities and optimize industrial and energy structures within cities such as Beijing, Langfang, Tianjin and Baoding. Furthermore, the authors recommend promoting sustainable intensification of agriculture and carefully balance between both economic development and ecological protection in Zhangjiakou and plain area.

The authors propose a zoning method based on the optimization of land use towards low-carbon development by combining “top-down” and “bottom-up” strategies and provide targeted governance suggestions for each region. This study provides policy implications to implement the regional low-carbon economic transition under the “double carbon” target in urban agglomerations in China.

Major land use changes can have a significant impact on the environment, e.g. increased leaching and run‐off losses of nutrients and water contamination. Nitrate (NO₃^–) can be easily leached and, when present at high concentrations in drinking water, can be a health hazard. This paper seeks to report an easy‐to‐use computer model designed to provide predictions of possible impacts on groundwater NO₃^– concentration on a regional scale.

The model takes into account NO₃^–‐N concentrations from various land use activities, land surface recharge rates (as affected by soil water retention capacity, land management, irrigation and rainfall), and mixing of surface recharge and river recharge. Spatial information on land use and groundwater recharge sources are lumped into groundwater management zones (100‐500 km²), and vertical concentration profiles of NO₃^– in groundwater are estimated from a one‐dimensional dispersion model. The model is applied to the 2,300 km² Central Canterbury Plains of New Zealand.

A scenario analysis for the Bankside groundwater management zone showed that the NO₃^–‐N concentration at the groundwater surface could increase from 7.8 mg N L^‐1 to 11.3 mg N L^‐1 if all the land used for sheep farming is replaced by dairy farming (increasing dairy land from 21 per cent to 64 per cent of the total land area). However, the impact of such land use changes on the NO₃^–‐N concentration 50 m below the groundwater surface was relatively small, resulting in an increase of NO₃^–‐N concentration from 0.4 to 0.5 mg N L^‐1. This is because of the significant mixing of surface recharge with river recharge at this depth.

The model can serve as a useful tool for first‐order estimation of possible trends of NO₃^–‐N concentration profiles in aquifers as a result of land use changes.

This study aims to present preliminary results from an integrated evaluation of electricity supply systems for rural areas using renewable energy technologies by means of a multi‐objective decision making method

Goal programming is applied to obtain the optimal system configuration meeting the electricity demand, based on the location's resource availability and taking diesel generation as the alternative of reference. The performance of the system is evaluated through four attributes: electricity generation costs, employment and two environmental impacts (CO₂ emissions and land use). The model is designed for isolated rural area belonging to the non‐interconnected zones of Colombia.

Application of the method showed that biomass conversion technology has the highest potential and that renewable energy systems offer better performance than diesel generation. Reductions of more than 10 percent in unit electricity costs, land use rates and CO₂ emissions can be achieved.

Inclusion of additional attributes and sensitivity analysis are matters of future research.

The methodology used in this study is an alternative means to perform evaluation of electricity supply systems integrating several aspects of technology and which is flexible enough so as to enable the inclusion of a wider scope of interests towards energy access targets.

Urban renewal projects provide an effective channel for adjusting land-use allocation and improving land-use efficiency, which effectively increases land supply. The purpose of this paper is to support the decision-making process of sustainable land use in urban renewal projects. A GIS-based framework, consisting of a planning support model and a land information database, has been developed in a typical high-density city – Hong Kong.

A qualitative and quantitative combined methodology is designed for this research. Several research methods such as expert interviews, focus group meetings, and case studies and technical approaches such as GIS, MCA, and AHP are adopted in this research.

General and sustainability criteria for land-use decision making in urban renewal along with associated data are identified, and an integrated approach to quantitatively assessing land-use suitability is developed.

The framework was developed in a loosely coupled form rather than a software package installed on a computer, and the development of the land information database was a time-consuming process as a large amount of data were collected, processed, and analyzed.

Application of the proposed framework is reported by showing analyzed results of land-use suitability. The framework proves a useful tool for both practitioners and researchers involved in sustainable land use for urban renewal.

The purpose of this paper is to explore how Monte Carlo Simulation (MCS) could have enhanced understanding of the risks involved in the financial strategy for revitalization of Rio de Janeiro’s central city based on the capture of value generated by government interventions.

The study first describes the process involved in developing the financial strategy and model without MCS. Then, it shows how the MCS could have been integrated into this process and evaluates its potential impacts on the quality of risk analysis.

If MCS is fully integrated into the decision-making process, it can serve as a heuristic tool that helps team members to better understand risks by generating forecasts of land value and other variables as a probability distributions. By showing the variance of the forecasted variable, MCS integrates elements of modern risk analysis into financial model development in a cost-effective manner.

MCS covers only the risks associated with the variables in the financial model. Events that seem extremely unlikely (i.e. “black swans”) can occur and must be assessed separately.

MCS can help analysts to understand the financial risks of large-scale development projects involving value capture, even in the prefeasibility stage.

By facilitating value capture, MCS could help close the financing gap for sustainable urban development and subsidies for lower income families.

The study “retrofits” MCS on a successfully completed financial prefeasibility study to assess its usefulness as a heuristic tool.

The authors aim to provide here an opinion on the state‐of‐the‐art of integrated ecological‐economic assessments of bioenergy under climate change, as well as the challenges along with their implications faced in planning adaptation at local scale.

Investments to reduce emissions must be made in the coming decades to avoid the risks posed by climate change. If these investments are made wisely, then costs will be manageable, stability in markets as well as energy security will be achieved, and even rural development and economic growth may be stimulated. The authors call attention to the need for modeling of climate change impacts by combining the outputs from appropriately designed crop simulation models with economic analyses. Combining natural science and economics in a compatible fashion at local scale will play an essential role in advancing communication and information exchange.

There are key differences in drivers or determinants of mitigation and adaptation potential and decisions at different scales, which means that different actors, different timescales and different spatial scales of decision making must be specifically considered. Understanding of the potential impacts of climate change requires disaggregation of the agricultural sector with appropriate detail. A critical trade‐off exists between area‐wide spatial coverage and an explicit consideration of local peculiarities.

The authors suggest that a much stronger effort must be made to meld natural science crop modeling approaches with economic analyses, to include spatially explicit consideration of conventional crop production along with 1st and 2nd generation bioenergy crops, and the evaluation not only of “best guess” scenarios of change, but also potential system impacts of extreme scenarios.