Mapping and web-based geovisualisation of suitable solar power plant sites in Zimbabwe: a current and futuristic approach

Predicting the joint effects of future climate and land use change on ecosystem health in the Middle Reaches of the Yangtze River Economic Belt, China

The impact of future land use and land cover changes (LULCC) on regional and global climate is one of the most challenging aspects of understanding anthropogenic climate change. We study the impacts of LULCC on regional climate in the southeastern U.S. by downscaling the NASA Goddard Institute for Space Studies global climate model E to the regional scale using a spectral nudging technique with the Weather Research and Forecasting Model. Climate‐relevant meteorological fields are compared for two southeastern U.S. LULCC scenarios to the current land use/cover for four seasons of the year 2050. In this work it is shown that reforestation of cropland in the southeastern U.S. tends to warm surface air by up to 0.5 K, while replacing forested land with cropland tends to cool the surface air by 0.5 K. Processes leading to this response are investigated and sensitivity analyses conducted. The sensitivity analysis shows that results are most sensitive to changes in albedo and the stomatal resistance. Evaporative cooling of croplands also plays an important role in regional climate. Implications of LULCC on air quality are discussed. Summertime warming associated with reforestation of croplands could increase the production of some secondary pollutants, while a higher boundary layer will decrease pollutant concentrations; wintertime warming may decrease emissions from biomass burning from wood stoves.

The significant natural energy sources for reducing the global usage of fossil fuels are renewable energy (RE) sources. Solar energy is a crucial and reliable RE source. Site selection for solar photovoltaic (PV) farms is a crucial issue in terms of spatial planning and RE policies. This study adopts a Geographic Information System (GIS)-based Multi-Influencing Factor (MIF) technique to enhance the precision of identifying and delineating optimal locations for solar PV farms. The choice of GIS and MIF is motivated by their ability to integrate diverse influencing factors, facilitating a holistic analysis of spatial data. The selected influencing factors include solar radiation, wind speed, Land Surface Temperature (LST), relative humidity, vegetation, elevation, land use, Euclidean distance from roads, and aspect. The optimal sites of solar PV power plant delineated revealed that ‘very low’ suitability of site covering 4.866% of the study area, ‘low’ suitability of site 13.190%, ‘moderate’ suitability of site 31.640%, ‘good’ suitability of site 32.347%, and ‘very good’ suitability of site for solar PV power plant encompassing 17.957% of the study area. The sensitivity analysis results show that the solar radiation, relative humidity, and elevation are the most effective on the accuracy of the prediction. The validation of the results shows the accuracy of solar PV power plant prediction using MIF technique in the study area was 81.80%. The integration of GIS and MIF not only enhances the accuracy of site suitability assessment but also provides a practical implementation strategy. This research offers valuable insights for renewable energy policymakers, urban planners, and other stakeholders seeking to identify and develop optimal locations for solar energy power farms in their respective regions.

Chapter 15 - Impacts of land use and climate change on streamflow and water balance of two sub-catchments of the Murrumbidgee River in South Eastern Australia

In western Victoria, Australia the water table and lake level in the Glenelg-Hopkins catchment have been declining for the last 15 years, and this is attributed to either the low rainfall over this time and/or a substantial change in land use. Stream flow modelling was carried out using monthly empirical water balance model (modified tanh function together with double mass curve analysis), on 37 stream gauges to assess whether the impact of land use change could be detected by a change in the magnitude of the resulting runoff. The empirical hydrological model was able to distinguish impact of land use change on stream flow from the climatic variables. There were substantial decreases in stream flow in the 1970s–1980s, probably related to increasing livestock densities in the region. Furthermore, the methodology can be a powerful tool to monitor and evaluate the possible impacts of future land use changes. It can be concluded that the use of such empirical hydrological modelling greatly improves the ability to analyse the impact of land use on catchment runoff. The model is a practical tool that can be readily used for identifying and quantifying the effect of landuse changes on catchment for water resource decision-making, which could be hardly possible using the time consuming, data hungry and expensive physical process models available.

Soil erosion is the predominant agent affecting ecosystem services in the Ethiopian highlands. However, land management interventions aimed at controlling erosion in the region are hampered, mainly by a lack of watershed-based appropriate management practices and anticipated climate changes. This study examined the effectiveness of different land use changes and management scenarios in decreasing runoff and sediment loss under current and future climates in the drought-prone humid watershed of the Ethiopian highlands. We employed a modeling approach integrating observed data at watershed and plot scales with Soil and Water Assessment Tool. In the first step, we evaluated the impact of land use changes between 2006 and 2017 on runoff and sediment loss. Then, we developed five land use and management scenarios based on watershed land capabilities and selected land management practices. Model parameters were modified based on runoff and sediment loss results obtained from experimental plots of biophysical and agronomical land management practices in the watershed. The runoff and sediment loss were simulated under current (2014-2019) and future climates (the 2050s) for each land use and management scenario. Results revealed that land use changes (mainly an increase in Acacia decurrens plantations by 206%) alone between 2006 and 2017 reduced runoff by 31% and sediment loss by 45%. Under the current climate, the five land use and management scenarios reduced runoff by 71-95% and sediment loss by 75-96% compared to the baseline scenario. Under the future climate (2050s), these scenarios decreased runoff by 48-90% and sediment loss by 54-91%. However, their effectiveness was slightly decreased (5-23%) as a result of increases in rainfall (10-46%) and mean temperature (1.7-1.9 °C) in the 2050s. The scenario of improving vegetation cover through forage production and plantations in appropriate areas plus best land management practices was the most effective and climate-resilient of the five scenarios. This study suggests that evaluating the impact of land use and management practices under future climate change shows promise for guiding effective and sustainable interventions to adapt to climate change.

Renewable energy sources are the most necessitated natural energy to reduce fossil fuels globally. Fossil fuel is the most valuable and limited resource on the planet, but on the other hand, renewable energy creates less pollution. Solar energy is the most effective renewable resource for daily use. Solar power plants are necessary for domestic and daily use. Remote sensing and geographic information technology (GIS) were used for this study to delineate the possible site selection of solar power plants in Kolkata and the surrounding area in West Bengal, India. The analytical hierarchy process (AHP) and the multi-criteria decision-making process (MCDA) were used for each weight calculation and ArcGIS v10.8 was applied for weighted overlay analysis (WOA) for delineation of the result. The site suitability map was developed using a pairwise comparison matrix and the weights were calculated for each criterion. The suitability map was divided into five categories, from not suitable to very highly suitable. A total of 474.21 km2 (10.69%) of the area was classified as very highly suitable whereas 249.54 km2 (5.62%) area was classified as not suitable because of the water area and east Kolkata wetland. A total of 1438.15 km2 (32.43%) of the area was classified as highly suitable for a solar power plant. The Kolkata megacity and water body locations were identified as moderate to not suitable sites. Very high and high-potential sites were identified 2 to 5 km from the central business district (CBD) location, which is Dharmotala. Renewable energy source is needed in the megacity of Kolkata. If solar power plants are contracted then the demand for fossil fuel will be reduced one day, and that will help the environment as well as the society in terms of sustainable development. This study result is helpful for administrators, urban planners, developers, and other stakeholders for the implementation and development of a new solar power plant in the study area.

To address Nigeria's electricity shortages and overreliance on traditional methods, solar power plants are being considered. However, selecting suitable sites for this purpose is critical and often poses a serious challenge considering a range of conflicting factors. In this study, the Analytical Hierarchy Process (AHP) technique and Geographic Information Systems (GIS) were combined to determine suitable sites for a solar electric power plant in Ewekoro Local Government Area (LGA). The approach considered road networks, transmission lines, slope, and land use as the key criteria as well as nineteen subcriteria for the site suitability analysis. The criteria and sub-criteria importance were weighted using AHP and the weights were inputted into the weighted overlay tool in the ArcGIS 10.4 for analysis. The resulting sub-criteria weights of land use are 3.5%, 6.8%, 10.6%, 16%, and 63.1% for built-up areas, waterbody, wetlands, rocky areas, and vegetation respectively. Based on the analysis, a suitability map was generated that categorized the study area as best suitable, suitable, and not suitable. On the map, 15% of the area was best suitable, 17% was suitable, and 68% was not suitable for solar power plants. In conclusion, the site suitability analysis of Ewekoro LGA for solar power plants has been evaluated and this approach can be extended to other areas in Nigeria where solar energy integration is of high priority.

In separate analyses of the impacts of land use change and climate change, a scenario-based approach using remote sensing and hydro-climatological data was developed to assess changes in hydrological indices. The data comprised three Landsat TM images (1988, 1998, 2008) and meteorological and hydrological data (1983–2012) for the Aligudarz and Doroud stations in the Marboreh watershed, Iran. The QUAC module and supervised classification maximum likelihood (ML) algorithm in ENVI 5.1 were used for remote sensing, the SWAT model for hydrological modelling and the Mann-Kendall and t test methods for statistical analysis. To create scenarios, the study period was divided into three decades (1983–1992, 1993–2002, 2003–2012) with clearly different land use/land cover (LULC). After hydrological modelling, 10 hydrological indices related to high and low flow indices (HDI and LDI) were analysed for seven scenarios developed by combining pre-defined climate periods and LULC maps. The major changes in land use were degradation of natural rangeland (− 18.49%) and increasing raid-fed farm area (+ 16.70%) and residential area (+ 0.80%). The Mann-Kendall test results showed a statistically significant (p < 0.05) decreasing trend in rainfall and flow during 1983–2012. In the scenarios evaluated, hydrological index trends were more sensitive to climate change than to LULC changes in the study area. Low flow indices were more affected than high flow indices in both land use and climate change scenarios. The results show little impact of land use change and indicate that climate change is the main driver of hydrological variations in the catchment. This is useful information in outlining future strategies for sustainable water resources management and policy decision-making in the Marboreh watershed.

Simulated impact of past and possible future land use changes on the hydrological response of the Northern German lowland ‘Hunte’ catchment

Distinguishing the impacts of land use and climate change on ecosystem services in a karst landscape in China

An integrated study of spatial multicriteria analysis and mathematical modelling for managed aquifer recharge site suitability mapping and site ranking at Northern Gaza coastal aquifer

The evaluation of suitable landfill sites is a complex process and requires various legislative, technical, social, and environmental criteria. Therefore, this study provides a management tool for identifying suitable sites for landfills through the integrated use of the analytic hierarchy process (AHP), geographic information systems (GISs), and remote sensing (RS). Accordingly, fourteen subcriteria were identified and grouped into physical (7), environmental (3), and socioeconomic (4) criteria and were weighed using pairwise comparison matrices (PCMs). The weighted linear combination (WLC) approach of maps allowed us to generate models and submodels of land suitability. From the territory of the districts of Chachapoyas and Huancas, 0.9% (1.71 km2), 71.1% (141.89 km2), 21.0% (41.86 km2), 0.0%, and 7.7% (14.21 km2) have highly suitable, moderately suitable, marginally suitable, unsuitable, and restricted conditions, respectively, for a landfill site. Twelve highly suitable sites were identified, of which three were selected based on their shape and the minimum area required for the operation of the landfill until 2040. In fact, this study proposes a management tool for decision‐makers (DMs) that improve the process of selecting landfill sites, supported by engineering and its applications for territorial sustainability.

Climate change and land use change are the two main factors affecting the regional water cycle and water resources management. However, runoff studies in the karst basin based on future scenario projections are still lacking. To fill this gap, this study proposes a framework consisting of a future land use simulation model (FLUS), an automated statistical downscaling model (ASD), a soil and water assessment tool (SWAT) and a multi-point calibration strategy. This frameword was used to investigate runoff changes under future climate and land use changes in karst watersheds. The Chengbi River basin, a typical karst region in southwest China, was selected as the study area. The ASD method was developed for climate change projections based on the CanESM5 climate model. Future land use scenarios were projected using the FLUS model and historical land use data. Finally, the SWAT model was calibrated using a multi-site calibration strategy and was used to predict future runoff from 2025–2100. The results show that: (1) the developed SWAT model obtained a Nash efficiency coefficient of 0.83, which can adequately capture the spatial heterogeneity characteristics of karst hydro-climate; (2) land use changes significantly in all three future scenarios, with the main phenomena being the interconversion of farmland and grassland in SSPs1-2.6, the interconversion of grassland, farmland and artificial surfaces in SSPs2-4.5 and the interconversion of woodland, grassland and artificial surfaces in SSPs5-8.5; (3) the average annual temperature will show an upward trend in the future, and the average annual precipitation will increase by 11.53–14.43% and (4) the future annual runoff will show a significant upward trend, with monthly runoff mainly concentrated in July–September. The variability and uncertainty of future runoff during the main-flood period may increase compared to the historical situation. The findings will benefit future water resources management and water security in the karst basin.

Global climate change and rapid urbanization have placed enormous pressure on the urban ecological environment worldwide. Urban green spaces, which are an important component of urban ecosystems, can maintain ecological and environmental sustainability and benefits, including biodiversity conservation and carbon sequestration. However, land use changes across urban landscapes, especially in plain urban areas with high development pressure, have significantly impacted the carbon sequestration efficiency of urban green spaces. Nevertheless, research examining the impact of land use change and development pressure on urban green spaces and carbon sequestration is relatively scarce. Understanding the carbon sequestration efficiency of urban green spaces and its determining factors will help predict future carbon capture trends within urban ecosystems and formulate more targeted sustainable urban planning and management strategies to improve urban carbon sink efficiency and achieve the goal of carbon neutrality. Therefore, to understand the factors affecting the carbon sequestration efficiency of urban green spaces, this paper used an integrated framework that combined the Carnegie–Ames–Stanford approach (CASA) model, landscape pattern index, multiple linear regression, and Markov–FLUS model. The study explored the impact of urban land use and land cover changes on carbon sequestration within the plain urban areas of Beijing at street scale. The results showed that, at street scale, there was a significant positive and negative correlation between the landscape pattern index and net primary productivity (NPP). In addition, the green spaces located in areas with more complex landscape structures had better carbon sequestration benefits. In addition, multiscenario carbon sequestration efficiency prediction suggested that the sustainable development (SD) scenario could achieve a positive increment of overall NPP. In contrast, the business-as-usual development (BD), the fast development (FD), and the low development (LD) scenarios showed a downward trend in NPP. This paper also proposed strategies for optimizing and enhancing green spaces within urban plain areas. Based on the strategies, the results guide decision making for sustainable urban green space planning that maintains the ecological, economic, and social integrity of urban landscapes during urbanization.