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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]

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]