Ecosystem services and disservices in the Luanhe River Basin in China under past, current and future land uses: implications for the sustainable development goals

Understanding how ecosystem services (ES) and ecosystem disservices (EDS) are affected by human-induced landscape changes is important to minimise trade-offs and maximise synergies between Sustainable Development Goals (SDGs) and targets, and for equitable development across governance scales. However, limited research investigates how ES and EDS can change under past, current, and future land uses. This study, conducted in the Luanhe River Basin (LRB), demonstrates the interaction between humans and the environment under past, current, and future land uses at the river basin scale in China, using a stakeholders’ participatory capacity matrix to characterise both ES and EDS. Results indicate that forests and water bodies provided the highest overall ES capacity, while the lowest scores were reached in built-up and unused land areas. Built-up land and cropland provided the highest overall EDS, while the lowest EDS scores were for water bodies. By applying the ecosystem services potential index (ESPI) and ecosystem disservices potential index (EDSPI), we found that the ESPI of all the ES declined from 1980 to 2018 and would continue to decline until 2030 without sustainable and conservation development strategies in the LRB. The EDSPI under all future scenarios in 2030 was projected to increase compared to the baseline in 1980. This study recommends establishing and implementing sustainable environmental protection policies and cross-regional and trans-provincial eco-compensation schemes for minimising trade-offs in ES. The study proposes an integrated research framework that could be useful for understanding the effect of historical and future human–environment interactions on ES and EDS, and SDGs achievement.

Development of an SDG interlinkages analysis model at the river basin scale: a case study in the Luanhe River Basin, China

While the Sustainable Development Goals (SDG) are broadly framed with 17 goals, the goals and their targets inherently connect with each other forming a complex system. Actions supporting one goal may influence progress in other goals, either positively (synergies) or negatively (trade-offs). Effective managing the synergies and trade-offs is a prerequisite for ensuring policy coherence. This is particular relevant at the river basin scale where the implementation of national policies may generate inequalities at the sub-basin levels, such as the upstream and the downstream. In the existing literature, there is still a lack of methodologies to assess the SDG interlinkages and their differences at the subnational levels. This paper presents a methodology on the development of an SDG interlinkages analysis model at the basin scale and its application to a case study in China’s Luanhe River Basin (LRB). Seven broad areas, namely land use and land cover change, climate change, ecosystem services, flood risks, water sector, urbanisation, and energy, were set as the scope of study. Through a systematic review, key elements of the SDG interlinkages system were identified and their interactions were mapped. The resulting generic SDG interlinkages model were validated with expert survey and stakeholders’ consultation and tailored to the LRB. Quantification of the SDG interlinkages was conducted for 27 counties in the LRB and demonstrated by the results of 3 selected counties located in the upstream, midstream and downstream areas, respectively. The methodology and its applications can be used to support integrated water resource management in river basins.

Study on the streamflow compensation characteristics of reservoirs in Luanhe River Basin based on Copula function

With the rapid development of economy and society, the contradiction between supply and demand of water resources is increasing. Efficient utilization and allocation of limited water resources are one of the main means to solve the above contradictions. In this paper, the multidimensional joint distribution of natural streamflow series in reservoirs is constructed by introducing the mixed Copula function, and the probability of wet and dry encounters between natural streamflow is analyzed. Luan River is located in the northeastern part of Hebei Province, China, taking the group of Panjiakou Reservoir, Douhe Reservoir and Yuqiao Reservoir in the downstream of Luan River Basin as an example, the probabilities of synchronous and asynchronous abundance and depletion of inflow from the reservoirs are calculated. The results show that the probability of natural streamflow series between reservoirs is 61.14% for wetness and dryness asynchronous, which has certain mutual compensation ability. Therefore, it is necessary to minimize the risk of water supply security in Tianjin, Tangshan and other cities, and strengthen the optimal joint water supply scheduling of reservoirs. The research results are reasonable and reliable, which can provide reference for water supply operation of other basins.

Large-scale flood risk assessment under different development strategies: the Luanhe River Basin in China

Increasing resilience to natural hazards and climate change is critical for achieving many Sustainable Development Goals (SDGs). In recent decades, China has experienced rapid economic development and became the second-largest economy in the world. This rapid economic expansion has led to large-scale changes in terrestrial (e.g., land use and land cover changes), aquatic (e.g., construction of reservoirs and artificial wetlands) and marine (e.g., land reclamation) environments across the country. Together with climate change, these changes may significantly influence flood risk and, in turn, compromise SDG achievements. The Luanhe River Basin (LRB) is one of the most afforested basins in North China and has undergone significant urbanisation and land use change since the 1950s. However, basin-wide flood risk assessment under different development scenarios has not been considered, although this is critically important to inform policy-making to manage the synergies and trade-offs between the SDGs and support long-term sustainable development. Using mainly open data, this paper introduces a new framework for systematically assessing flood risk under different social and economic development scenarios. A series of model simulations are performed to investigate the flood risk under different land use change scenarios projected to 2030 to reflect different development strategies. The results are systematically analysed and compared with the baseline simulation based on the current land use and climate conditions. Further investigations are also provided to consider the impact of climate change and the construction of dams and reservoirs. The results potentially provide important guidance to inform future development strategies to maximise the synergies and minimise the trade-offs between various SDGs in LRB.

Modelling land system evolution and dynamics of terrestrial carbon stocks in the Luanhe River Basin, China: a scenario analysis of trade-offs and synergies between sustainable development goals

A more holistic understanding of land use and land cover (LULC) will help minimise trade-offs and maximise synergies, and lead to improved future land use management strategies for the attainment of Sustainable Development Goals (SDGs). However, current assessments of future LULC changes rarely focus on the multiple demands for goods and services, which are related to the synergies and trade-offs between SDGs and their targets. In this study, the land system (combinations of land cover and land use intensity) evolution trajectories of the Luanhe River Basin (LRB), China, and major challenges that the LRB may face in 2030, were explored by applying the CLUMondo and InVEST models. The results indicate that the LRB is likely to experience agricultural intensification and urban growth under all four scenarios that were explored. The cropland intensity and the urban growth rate were much higher under the historical trend (Trend) scenario compared to those with more planning interventions (Expansion, Sustainability, and Conservation scenarios). Unless the forest area and biodiversity conservation targets are implemented (Conservation scenario), the forest areas are projected to decrease by 2030. The results indicate that water scarcity in the LRB is likely to increase under all scenarios, and the carbon storage will increase under the Conservation scenario but decrease under all other scenarios by 2030. Our methodological framework and findings can guide regional sustainable development in the LRB and other large river basins in China, and will be valuable for policy and planning purposes to the pursuance of SDGs at the sub-national scale.

Modelling dynamics of land use and ecosystem services changes in the Luanhe River Basin in China

<p>Quantifying land use dynamics is central to evaluate changes in terrestrial and aquatic ecosystems. It also allows for understanding how ecosystem services (ES) and ecosystem disservices (EDS) are affected by human interventions in the landscape. Finally, it can lead to the development of improved future land use management strategies for the achievement of the Sustainable Development Goals (SDGs). The Luanhe River Basin (LRB) is the most afforested river basin in North China and provides multiple ecosystem services which are related to several SDGs (e.g. SDG 6: Clean Water and Sanitation, 7: Affordable and Clean Energy, and 13: Climate Action). In this study, four scenarios: Trend, Expansion, Sustainability, and Conservation were developed based on different socioeconomic development and environmental protection targets as well as local plans and policies. Local stakeholders were consulted to develop these scenarios and to explore land use dynamics of the LRB and major challenges that the river basin may face by 2030. Land use change was modelled with CLUMondo and ES and EDS were characterised using capacity matrices. The ecosystem services potential index (ESPI) and ecosystem disservices potential index (EDSPI) was calculated, and ES and EDS hotspots and coldspots were identified. The study found that forests and water bodies provided the highest overall ES capacity, while the lowest scores were recorded for built-up and unused land areas. Built-up land and cropland provided the highest overall EDS capacity, while the lowest EDS scores were for water bodies. The forests and water bodies, which were widespread in the upper-middle reaches of the basin, were hotspots of provisioning services, regulating services, cultural services and ecological integrity, while the hotspots of EDS were concentrated in the built-up land areas and the croplands, which were mainly distributed in the downstream of the LRB. Modelling results indicated that the LRB was likely to experience agricultural (crop and livestock) intensification and urban growth under all four future scenarios. The cropland intensity and the urban growth rate were much higher under the historical trend (Trend) scenario compared to those with more planning interventions (Expansion, Sustainability, and Conservation scenarios). The most significant increase of livestock density in grassland was projected under the Expansion scenario. Unless the forest area and biodiversity conservation targets are implemented (Conservation scenarios), the forest areas are projected to decrease under three scenarios by 2030. The ESPI of all the ES declined from 1980 to 2018 and would continue to decline until 2030 without sustainable and conservation development strategies. Compared with the EDSPI in 1980, the EDSPI under all future scenarios in 2030 was projected to increase. This study calls for establishing and implementing sustainable environmental protection policies as well as cross-regional and trans-provincial eco-compensation schemes for minimising trade-offs in ES. The methodological framework and findings of this study can guide regional sustainable development and rational utilisation of land resources in the LRB and other comparable river basins, and will be valuable for policy and planning purposes to the pursuance of SDGs at the sub-national scale.</p>

Combined effects of predicted climate and land use changes on future hydrological droughts in the Luanhe River basin, China

Drought can be impacted by both climate change and land use change in different ways. Thus, in order to predict future drought conditions, hydrological simulations as an ideal means, can be used to account for both projected climate change and projected land use change. In this study, projected climate and land use changes were integrated with the SWAT (Soil and Water Assessment Tool) model to estimate the combined impact of climate and land use projections on hydrological droughts in the Luanhe River basin. We presented that the measured runoff and the remote sensing inversion of soil water content were simultaneously used to validate the model to ensure the reliability of model parameters. Following the calibration and validation, the SWAT model was forced with downscaled precipitation and temperature outputs from a suite of nine Global Climate Models (GCMs) based on the CMIP5, corresponding to three different representative concentration pathways (RCP 2.6, RCP 4.5 and 8.5) for three distinct time periods: 2011–2040, 2041–2070 and 2071–2100, referred to as early-century, mid-century and late-century, respectively, and the land use predicted by CA-Markov model in the same future periods. Hydrological droughts were quantified using the Standardized Runoff Index (SRI). Compared to the baseline scenario (1961–1990), mild drought occurred more frequently during the next three periods (except the 2080s under the RCP2.6 emission scenario). Under the RCP8.5 emission scenario, the probability of severe drought or above occurring in the 2080s increased, the duration prolonged and the severity increased. Under the RCP2.6 scenario, the upper central region of the Luanhe river in the 2020s and upper reaches of the Luanhe river in the 2080s, were more likely to suffer extreme drought events. And under the RCP8.5 scenario, the middle and lower Luanhe river in the 2080s, were more likely to suffer these conditions.

The Influence of Climate, Soil Properties and Vegetation on Soil Nitrogen in Sloping Farmland

Soil nitrogen in farmland ecosystems is affected by climate, soil physical and chemical properties and planting activities. To clarify the effects of these factors on soil nitrogen in sloping farmland quantitatively, the distribution of soil total nitrogen (TN) content, nitrate nitrogen (NO3-N) content and ammonium nitrogen (NH4-N) content at depth of 0–100 cm on 11 profiles of the Luanhe River Basin were analyzed. Meanwhile, soil physical and chemical properties, climatic factors and NDVI (Normalized Difference Vegetation Index) were used to construct a structural equation which reflected the influence mechanism of environmental factors on soil nitrogen concentration. The results showed that TN and NO3-N content decreased with the increase of soil depth in the Luanhe River Basin, while the variation of NH4-N content with soil depth was not obvious. Soil organic carbon (SOC) content, soil pH, soil area average particle size (SMD) and NDVI6 (NDVI of June) explained variation of TN content by 77.4%. SOC was the most important environmental factor contributing to the variation of TN content. NDVI5 (NDVI of May), annual average precipitation (MAP), soil pH and SOC explained 49.1% variation of NO3-N content. Among all environmental factors, only NDVI8 (NDVI of August) had significant correlation with soil NH4-N content, which explained the change of NH4-N content by 24.2%. The results showed that soil nitrogen content in the sloping farmland ecosystem was mainly affected by natural factors such as soil parent material and climate.