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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 southern rivers of Peru originate in the Andes Mountains and flow in a southwestern direction to the Pacific Ocean through one of the most hyper-arid regions of the world. During each sub-equatorial summer from December to February, rains and snow melt in the Andes increase the streamflow in these rivers, even as they pass through the 100 km arid zone to the ocean. This study quantified seasonal dynamics of 34 trace metal elements (TM) and other constituent concentrations in four southern river basins of Peru (Chili-Quilca, Tambo, Camana-Majes-Colca, and Ocoña) during 2019–2020. Consistent with previous studies, we observed that: (1) the river water in the southern basins had relatively high concentrations of B, As, Fe, Al, Mn, P, Pb and Ni, with As the most ubiquitous toxic TM in all the basins, often detected at concentrations surpassing Peruvian and USEPA regulated concentrations; and (2) basins with the most to least toxic TM contamination were the Tambo > Chili-Quilca > Camana-Majes-Colca > Ocoña. Seasonal streamflow strongly influenced the concentrations of twenty TM, with 15 TM (Al, Au, Ba, Cd, Co, Cu, Fe, Gd, Mn, Ni, P, Pb, Ti, Yb and Zr) consistently higher in the wet season, and with As, B, Ge, Li, and Pd higher in the dry season. Our results improve the understanding of seasonal variability and vulnerability in western Andes superficial water sources, which are highly influenced by both local geogenic and anthropogenic conditions. A Spanish translation of this paper is available in the online Supplementary Material. [Display omitted] • Arsenic is the most ubiquitous contaminant in surface waters of Southern Peru. • Al, Fe, As, B, Mn, P, Pb, and Ni exceeded the Peruvian water quality regulation. • Out of 34 metals studied, 14 showed a strong seasonal behavior (e.g., As, Pb and B). • Total recoverable metals trended better rather than dissolved metal with season. [ABSTRACT FROM AUTHOR]

Groundwater markets improve the agricultural economy by transferring water entitlements from low-efficient users to high-efficient ones to maximize productivity. Aiming at developing an efficient groundwater market, the environmental effects of the market mechanism should be assessed, and a reliable method for monitoring water consumption needs to be employed. Toward this end, this paper proposes three annual smart groundwater market mechanisms to maximize water net benefits, minimize groundwater withdrawal, and precisely measure water consumption in agricultural fields. To guarantee the aquifer's safe yield in each mechanism, a groundwater simulation model (i.e., Groundwater Modeling System (GMS)) is used to control groundwater table drawdown at the end of the planning horizon. In addition, the fields' evapotranspiration (ET) is estimated using Surface Energy Balance Algorithm for Land (SEBAL) and Mapping Evapo Transpiration at high Resolution with Internalized Calibration (METRIC) algorithm to measure the net groundwater consumption during the market. In this regard, we evaluated the algorithms' performances using observed data from a local lysimeter. They are applied to the Nough plain in Iran to assess the effectiveness of the proposed market framework. The findings illustrate their efficiency in recovering approximately 80% (23.33 million cubic meters (MCM)) of groundwater loss due to overexploitation in the study area and increasing the users' annual benefits by 10.6% compared to the non-market condition. In addition, results imply that the METRIC model approximates daily crop ET with a higher accuracy level than the SEBAL model with RMSE, MAE, and Percentage Error of 0.37 mm/day, 0.32 mm/day, and 14.92%, respectively. This research revealed that the proposed market framework is a powerful tool for reallocating water entitlements and increasing water productivity in arid and semi-arid regions. • A groundwater market is proposed to promote economic and environmental situation. • The uncertainty of available water is incorporated in the proposed methodolgoy • Designed market mechanisms recover nearly 85% of groundwater loss in the study area. • The market framework raises the economic benefit by 128.7 billion rials annually. • METRIC algorithm approximates daily crop evapotranspiration with RMSE of 0.37 mm. [ABSTRACT FROM AUTHOR]

Located in the hinterland of the Eurasian continent, the inland areas of northwestern China have an arid climate and are confronted with continuing challenges in water resources quantity and quality. Reclaimed water plays an important role in maintaining the sustainable use of urban water resources, especially in arid regions. In this paper, a system dynamics urban reclaimed water model (SDURWM) considering the status of arid regions in northwestern China was constructed. The supply and demand balance index (RWB) and the utilization efficiency index (RWUE) of reclaimed water were proposed as evaluation indicators. The potential of reclaimed water utilization (2016–2025) in three typical cities with similar natural environments and population sizes but with large economic differences were estimated by the SD model. Then the relevant values of reclaimed water quota, supply and resident awareness were adjusted within the range of 10%–20%. The predicted results from intervention demonstrate that the RWB of three cities will be closer or maintain to the ideal value, and that the RWUE will increase by about 0.1, compared with the non-intervention results. This indicates that a minor change of the targeted policies can invigorate the capacity of reclaimed water use in droughty cities. This paper provides some effective solutions for the government's planning of developing the potential of reclaimed water. • Established a SD model for urban reclaimed water utilization in arid areas. • Proposed RWB and RWUE for evaluating the comprehensive utilization potential of reclaimed water. • Explored targeted measures to improve the utilization of reclaimed water in typical arid cities of northwest China. [ABSTRACT FROM AUTHOR]

Abstract: Recurrent droughts in arid and semi-arid regions are already rendering agricultural production, mainstay of subsistence livelihoods, uncertain. In order to mitigate the impact of drought, agricultural organizations must increase their capacity to adapt. Institutional adaptation refers to the creation of an effective, long-term government institution or set of institutions in charge of planning and policy, and its capacity to develop, revise, and execute drought policies. Using the Fars Agricultural Organization in Iran, as a case study, this paper explores the institutional capacities and capabilities, necessary to adapt to the drought conditions. The STAIR model was used as a conceptual tool, and the Bayesian network and Partial Least Squares (PLS) path modeling was applied to explain the mechanisms by which organizational capacities influence drought management. A survey of 309 randomly selected managers and specialists indicated serious weaknesses in the ability of the organization to apply adaptation strategies effectively. Analysis of the causal models illustrated that organizational culture and resources and infrastructure significantly influenced drought management performance. Moreover, managers and specialists perceived human resources and strategy, goals, and action plan, respectively, as the main drivers of institutional adaptation to drought conditions. Recommendations and implications for drought management policy are offered to increase organizational adaptation to drought and reduce the subsequent sufferings. [Copyright &y& Elsevier]

Surface water is one of the constraining resources for herbivore populations in semi-arid regions. Artificial waterpoints are constructed by wildlife managers to supplement natural water supplies, to support herbivore populations. The aim of this paper is to analyse how a landowner may realize his ecological and economic goals by manipulating waterpoints for the management of an elephant population, a water-dependent species in the presence of water-independent species. We develop a theoretical bio-economic framework to analyse the optimization of wildlife management objectives (in this case revenue generation from both consumptive and non-consumptive use and biodiversity conservation), using waterpoint construction as a control variable. The model provides a bio-economic framework for analysing optimization problems where a control has direct effects on one herbivore species but indirect effects on the other. A landowner may be interested only in maximization of profits either from elephant offtake and/or tourism revenue, ignoring the negative effects that could be brought about by elephants to biodiversity. If the landowner does not take the indirect effects of waterpoints into consideration, then the game reserve management, as the authority entrusted with the sustainable management of the game reserve, might use economic instruments such as subsidies or taxes to the landowners to enforce sound waterpoint management. [Copyright &y& Elsevier]

Abstract: Riparian zones are deemed significant due to their interception capability of non-point source impacts and the maintenance of ecosystem integrity region wide. To improve classification and change detection of riparian buffers, this paper developed an evolutionary computational, supervised classification method – the RIparian Classification Algorithm (RICAL) – to conduct the seasonal change detection of riparian zones in a vast semi-arid watershed, South Texas. RICAL uniquely demonstrates an integrative effort to incorporate both vegetation indices and soil moisture images derived from LANDSAT 5 TM and RADARSAT-1 satellite images, respectively. First, an estimation of soil moisture based on RADARSAT-1 Synthetic Aperture Radar (SAR) images was conducted via the first-stage genetic programming (GP) practice. Second, for the statistical analyses and image classification, eight vegetation indices were prepared based on reflectance factors that were calculated as the response of the instrument on LANDSAT. These spectral vegetation indices were then independently used for discriminate analysis along with soil moisture images to classify the riparian zones via the second-stage GP practice. The practical implementation was assessed by a case study in the Choke Canyon Reservoir Watershed (CCRW), South Texas, which is mostly agricultural and range land in a semi-arid coastal environment. To enhance the application potential, a combination of Iterative Self-Organizing Data Analysis Techniques (ISODATA) and maximum likelihood supervised classification was also performed for spectral discrimination and classification of riparian varieties comparatively. Research findings show that the RICAL algorithm may yield around 90% accuracy based on the unseen ground data. But using different vegetation indices would not significantly improve the final quality of the spectral discrimination and classification. Such practices may lead to the formulation of more effective management strategies for the handling of non-point source pollution, bird habitat monitoring, and grazing and live stock management in the future. [Copyright &y& Elsevier]

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]

This paper examines variation in local perceptions of risk in semi-arid Tanzania, identifying factors that influence local perceptions of problems and testing the feasibility of risk mapping as a technique. Twelve villages in six districts were visited between February and April 2001. Villagers were asked about their worries and concerns in providing for themselves and their families using a risk questionnaire. The responses were grouped into 21 categories of problem and incidence and severity indices were calculated for each category.Most problems were associated with the availability of natural resources on which livelihoods depend but others related to human and social capital assets. In addition to environmental factors, livelihood strategy and gender both influenced people''s perceptions of risk. Problems of irrigation and weather, for example, were important for agricultural communities while problems relating to livestock diseases, access to land and hunger were more important in pastoral communities. The risks cited by men and women generally reflected their traditional roles in society. Very broadly, the risks associated with natural capital tended to be seen as higher by men while women mentioned more problems relating to human and social capital. However, this was not always the case. Problems linked to finance, traditionally the concern of men, were ranked similarly by men and women.In projects designed to facilitate community management and control over common pool resources, the identification of common interests is particularly important. Risk mapping can provide a cost-effective way of gaining insights to help improve research design and to inform policy development. [Copyright &y& Elsevier]