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The effects of global climate change and human activities are anticipated to significantly impact ecosystem services (ESs), particularly in urban agglomerations of arid regions. This paper proposes a framework integrating the dynamic Bayesian network (DBN), system dynamics (SD) model, patch generation land use simulation (PLUS) model, and the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model for predicting land use change and optimizing ESs spatial patterns that is built upon the SSP-RCP scenarios from CMIP6. This framework is applied to the oasis urban agglomeration on the northern slope of the Tianshan Mountains in Xinjiang (UANSTM), China. The findings indicate that both the SD model and PLUS model can accurately forecast the distribution of future land use. The SD model shows a relative error of less than 2.32%, while the PLUS model demonstrates a Kappa coefficient of 0.89. The land use pattern displays obvious spatial heterogeneity under different climate scenarios. The expansion of cultivated land and construction land is the main form of land use change in UANSTM in the future. The DBN model proficiently simulates the interactive relationships between ESs and diverse factors. The classification error rates for net primary productivity (NPP), habitat quality (HQ), water yield (WY), and soil retention (SR) are 20.04%, 3.47%, 4.45%, and 13.42%, respectively. The prediction and diagnosis of DBN determine the optimal ESs development scenario and the optimal ESs region in the study area. It is found that the majority of ESs in UANSTM are predominantly influenced by natural factors with the exception of HQ. The socio-economic development plays a minor role in such urban agglomerations. This study offers significant insights that can contribute to the fields of ecological protection and land use planning in arid urban agglomerations worldwide. • An integrated framework combining DBN, SD, PLUS and InVEST models was proposed. • Impact of natural and socioeconomic factors on ESs was determined under climate scenarios. • The spatial pattern of ESs was optimized and partitioned using DBNs. • ESs in arid oasis urban agglomerations are mainly affected by natural factors. [ABSTRACT FROM AUTHOR]

The aspirational goal of a land degradation neutral world, to be realized by reducing the rate of land degradation and increasing the rate of restoration of degraded land, was agreed at the Rio+20 Conference in 2012. This paper evaluates the feasibility of introducing a Land Degradation Neutral (LDN) scheme as an activity of the United Nations Convention to Combat Desertification (UNCCD). It concludes that national and international implementation would involve political, organizational and technological challenges. Monitoring restoration of desertified land by revegetation would be feasible immediately, but monitoring cuts in national rates of desertification would not, because no baseline rates are currently available; national and international scientific capacities to measure desertification are limited; and further scientific knowledge is required to supplement existing knowledge of desertification processes and of land use and land cover change processes generally. This paper therefore suggests introducing an LDN scheme in phases. Phase 1 would focus on restoring degraded lands, improving national land use planning systems, and establishing international and national monitoring capacities. Phase 2 would reduce desertification rates with the help of fully integrated land use planning and monitoring systems. Phase 3 would set a target year for realizing an LDN goal, based on experiences in Phases 1 and 2. All three phases would be informed by accessing existing scientific knowledge, and gaining new knowledge by launching a scientific LDN process that can evolve in parallel with the political process. [ABSTRACT FROM AUTHOR]

Abstract Past water resource developments in dryland regions rarely estimated the full suite of environmental and social impacts arising from damming and diverting water for food production. Nowadays there is a greater focus on sustainable resource development which considers the economic, social and environmental costs and benefits. A challenge is to apply tools and methods which can capture the often disparate knowledge and data describing many costs and benefits. This paper describes a proof of concept application of a large Bayesian Decision Net to estimate the total utility of water resource development according to criteria of social, economic and environmental sustainability. We focus on two water-scarce catchments in remote northern Australia which are under investigation for development. The study catchments contain a diverse set of ecosystem services and socio-cultural values, including important Indigenous values and high value freshwater ecosystems. The Bayesian Decision Net was shown to have many properties that made it useful for performing a social, economic and environmental sustainability assessment, in particular its ease of construction; its ability to handle quantitative and qualitative data types; its preservation of system knowledge and; its ease of use in aiding decision making. From the perspective of the sustainability assessment in our case study, the total utility of water resource development for new irrigation is negative in both the studied catchments. The overall utility of water resource development could be positive if irrigation development is highly sensitive to the environment and there are very low environmental impacts, and much higher net economic returns to irrigators eventuate, possibly through higher commodity prices, lower capital costs of irrigation development or some combination of both. Highlights • Development of water resources involves trade-offs between economy and environment. • Integrated social-environment-economy sustainability (SEES) assessments support trade-offs analyses. • Bayesian Decision Networks (BDNs) support SEES assessments with diverse data types. • BDN applied to irrigation development scenarios of two remote catchments in north Australia. • The economic and ecosystem service benefits of the case study irrigation developments are questionable. [ABSTRACT FROM AUTHOR]

The paper focusses on the impact on dryland ecosystems of conflicting governance in the regulations of land use, water for irrigation and electric energy from photovoltaic installations (PV). The research uses the empirical results of a panel data model based on long time series that enable sensitivity of the main crops to energy cost and the viability of the solar panel system connected to the grid to be identified. We present evidence of the private and social benefits of investments in PV to improve the gross margin of farmers and decrease the carbon footprint of the irrigated areas. Relevant regional disparities in the sensitivity of the main crops explain the regional competition for low-cost water resources and the social conflicts associated with water governance. The Feed-In Tariff system for a PV system is evaluated as a tool to reach clean energy targets and preserve the populations working and living in irrigated drylands. An evaluation of the water desalination plants based on PV is analysed as an alternative to balance the hydric resources of intensive irrigated systems. The main conclusion is that coordinated regulation in energy and water policies may improve farmers' profitability and accelerate the speed in reaching environmental targets in drylands. • The paper assesses the economic viability of grid-connected photovoltaic installations of principal crops. • Since the liberalisation of the energy market, the electricity bill of irrigators become substantially higher. • Adaptation to climate change means to switch to PV irrigated systems to preserve gross land margins. • The contradictory and time unstable regulations send conflicting signals slowing the path to a clean irrigation system. • Our main conclusion is that the European Commission has a relevant task in coordinating water and energy regulations in arid lands. [ABSTRACT FROM AUTHOR]

Hydrological data and total phosphorus (TP) concentration at reservoirs' outlet were combined in a transient complete-mix model to obtain mean input loads and inlet concentration-flow relationships. This approach was designed to investigate the issue of phosphorus pollution in semiarid regions with intermittent rivers. The methodology was applied for twenty reservoirs in the State of Ceará, Brazilian semiarid. The modeled TP loads correlated well (R2 = 0.74) with reference loads estimated from environmental inventories, with only 10% of underestimated results. The average input loads per unit area of the catchments ranged from about 4 to 40 kg km−2 yr−1, which were considerably lower than the national average of about 500 kg km−2 yr−1. This was attributed to lower precipitation indexes, intermittent river regime and a high-density reservoir network, peculiar of the Brazilian semiarid. Meanwhile, the input load per unit area of a small and highly populated urban catchment, with higher precipitation indexes and deficient sanitation was substantially higher (2626 kg km−2 yr−1). Moreover, the fitted TP concentration-flow relationships directly reflected different TP input sources: strong u-shaped behavior marked the curves of highly non-point source dominated catchments, whereas a dilution pattern prevailed in those with significant point source inputs. The model validation with measured riverine TP concentration reached a NSE of 0.63. However, peak values in TP concentration during low flow rates sensitively affected the fitting of the models. In spite of non-point source dominance in the catchments, some relationships presented a slight signal of this use type. The variation range of the fitting parameters in comparison with other studies, as well the expected behavior of the curves in light of land use characteristics, strongly support the methodology applied in this study. The proposed approach will potentially help address the TP issue in tropical semiarid regions. Furthermore, the paper presents a simple way to deal with the challenging lack of monitored data in such environments. [Display omitted] • A mass-balance approach was designed to model TP inputs to tropical semiarid reservoirs. • Catchment usage was evaluated to identify TP sources and validate the proposed model. • TP loads were significantly lower than observed in other non-semiarid areas. • Precipitation, catchment area, river intermittence and reservoir network affected TP loads. • Different TP-inflow models were adjusted for PS and NPS dominated catchments. [ABSTRACT FROM AUTHOR]

In arid and semi-arid regions, unregulated land use changes as a result of poor planning, and the expansion of agricultural and livestock activities increase the risk of desertification and other potentially severe environmental impacts. Several consequences of improper land management practices are soil deterioration and erosion, which may be intensified by meteorological events. This paper presents a historical evaluation of the temporal and spatial evolution of soil deterioration in the southern Chihuahuan Desert in Mexico. A multi-temporal analysis of the study area during the 1995–2016 period was carried out using satellite data (Landsat series). Two seasons were analyzed to determine the influence of external events such as rainfall and wind: dry and rainy. The identification of soil conditions was based on the Brightness Index (BI) considering the complete satellite data set. The soil conditions were classified into five categories according to their reflectance values: highly deteriorated, deteriorated, in the process of being deteriorated, in good condition and other (clouds, water, non-soil). The change detection maps clearly show a growing trend wherein areas of deteriorated and eroded soil increase over time. Agriculture and strong winds are the two main factors involved in the soil deterioration process of the study region. • Deficient agricultural practices and strong winds precursors to desertification. • Spatial-temporal identification of deteriorated soil in arid/semi-arid zones. • Spectral analysis based method for categorization of soil conditions. • Comparative analysis of sensitivity in rainy and dry seasons. [ABSTRACT FROM AUTHOR]