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1.
J Environ Manage ; 362: 121299, 2024 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-38830283

RESUMO

Hydrological forecasting is of great importance for water resources management and planning, especially given the increasing occurrence of extreme events such as floods and droughts. The physics-informed machine learning (PIML) models effectively integrate conceptual hydrologic models with machine learning (ML) models. In this process, the intermediate variables of PIML models serve as bridges between inputs and outputs, while the impact of intermediate variables on the performance of PIML models remains unclear. To fill this knowledge gap, this study aims to encompass the construction of PIML models based on various hydrologic models, conduct comparative analyses of different intermediate variables based on a case study of 205 CAMELS basins, and further explore the relationship between the performance of PIML models and catchment characteristics. The optimal ML model for constructing PIML is first selected among four ML models within the 205 basins. The PIML models are then developed based on five monthly water balance models, namely TM, XM, MEP, SLM, and TVGM. To quantify the potential impact of difference in intermediate variables, two sets of experiments are further designed and performed, namely S1 with actual evapotranspiration as the intermediate variable and S2 with soil moisture as the intermediate variable. Results show that five PIML models generally outperformed the optimal standalone ML models, i.e., the Lasso model. Specifically, regardless of the choice of intermediate variables, the PIML-XM model consistently outperformed the other models within the same basins. Almost all constructed PIML models are affected by the intermediate variables in monthly runoff simulations. Typically, S1 exhibited better performance compared to S2. A greater impact of aridity index, forest fraction, and catchment area on model performance is observed in S2. These findings improve our understanding of constructing PIML models in hydrology by emphasizing their excellent performance in runoff simulations and highlighting the importance of intermediate variables.


Assuntos
Hidrologia , Aprendizado de Máquina , Modelos Teóricos
2.
J Environ Manage ; 362: 121073, 2024 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-38833926

RESUMO

Hydrologic-hydraulic modelling of urban catchment is an asset for land managers to simulate Sustainable Urban Drainage Systems (SUDS) implementation to fulfil combined sewer overflow (CSO) regulations. This review aims to assess the current practices in modelling SUDS scenarios at large scale for CSO mitigation encompassing every stage of the modelling process from the choice of the equation to the validation of the initial state of the urban system, right through to the elaboration, modelling, and selection of SUDS scenarios to evaluate their performance on CSO. Through a quantitative and qualitative analysis of 50 published studies, we found a diversity of choices when modelling the status quo of the urban system. Authors generally do not explain the modelling processes of slow components (deep infiltration, groundwater infiltration) and interconnexion between SUDS and the sewer system. In addition, only a few authors explain how CSO structures are modelled. Furthermore, the modelling of SUDS implementation at catchment scale is highlighted in the 50 studies retrieved with three different approaches going from simplified to detailed. SUDS modelling choices seem to be consistent with the objectives: studies focusing on dealing with several objectives at the time typically opt for a complex system configuration that includes the surface processes, network, CSO, SUDS, and often the soil and/or groundwater components. Conversely, authors who have selected a basic configuration generally aim to address a single, straightforward question (e.g., which type of SUDS). However, elaboration and selection of scenarios for CSO mitigation is mainly based on local constraints, which does not allow hydrological performance to be directly optimised. In conclusion, to improve current practices in modelling SUDS scenarios at large scale for CSO mitigation, authors suggest to: (i) improve clear practices of CSO modelling, calibration and validation at the urban catchment scale, (ii) develop methods to optimize the performance of scenarios for CSO mitigation using hydrological drivers, and (iii) improve parsimonious and user-friendly models to simulate SUDS scenarios in a context of data scarcity.


Assuntos
Modelos Teóricos , Esgotos , Água Subterrânea , Hidrologia
3.
J Environ Manage ; 362: 121284, 2024 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-38838538

RESUMO

Future changes in land use/land cover (LULC) and climate (CC) affect watershed hydrology. Despite past research on estimating such changes, studies on the impacts of both these nonstationary stressors on urban watersheds have been limited. Urban watersheds have several important details such as hydraulic infrastructure that call for fine-scale models to predict the impacts of LULC and CC on watershed hydrology. In this paper, a fine-scale hydrologic model-Personal Computer Storm Water Management Model (PCSWMM)-was applied to predict the individual and joint impacts of LULC changes and CC on surface runoff attributes (peak and volume) in 3800 urban subwatersheds in Midwest Florida. The subwatersheds a range of characteristics in terms of drainage area, surface imperviousness, ground slope and LULC distribution. The PCSWMM also represented several hydraulic structures (e.g., ponds and pipes) across the subwatersheds. We analyzed changes in the runoff attributes to determine which stressor is most responsible for the changes and what subwatersheds are mostly sensitive to such changes. Six 24-h design rainfall events (5- to 200-year recurrence intervals) were studied under historical (2010) and future (year 2070) climate and LULC. We evaluated the response of the subwatersheds in terms of runoff peak and volume to the design rainfall events using the PCSWMM. The results indicated that, overall, CC has a greater impact on the runoff attributes than LULC change. We also found that LULC and climate induced changes in runoff are generally more pronounced in greater recurrence intervals and subwatersheds with smaller drainage areas and milder slopes. However, no relationship was found between the changes in runoff and original subwatershed imperviousness; this can be due to the small increase in urban land cover projected for the study area. This research helps urban planners and floodplain managers identify the required strategies to protect urban watersheds against future LULC change and CC.


Assuntos
Hidrologia , Florida , Mudança Climática , Modelos Teóricos , Movimentos da Água , Clima , Chuva
4.
Ying Yong Sheng Tai Xue Bao ; 35(4): 985-996, 2024 Apr 18.
Artigo em Chinês | MEDLINE | ID: mdl-38884233

RESUMO

The southwestern region of China is the largest exposed karst area in the world and serves as an important ecological security barrier for the upstream of Yangtze River and Pearl River. Different from the critical zone of non-karst areas, the epikarst, formed by an interwoven network of denudation pores, is the core area of karst critical zone. Water is the most active component that participates in internal material cycle and energy flow within the critical zone. We reviewed relevant research conducted in the southwestern region from three aspects: the characte-rization of critical zone structure, the hydrological processes of soil-epikarst system, and their model simulations. We further proposed potential research hotpots. The main approach involved multi-scale and multi-method integrated observations, as well as interdisciplinary collaboration. Precisely characterizing the eco-hydrological processes of the vegetation-soil-epikarst coupling system was a new trend in the future research. This review would provide scientific reference for further studies on hydrological processes in critical zones and regional hydrological water resource management in karst areas.


Assuntos
Ecossistema , Hidrologia , China , Solo/química , Movimentos da Água , Rios , Água Subterrânea , Conservação dos Recursos Hídricos/métodos , Monitoramento Ambiental
5.
Environ Monit Assess ; 196(7): 624, 2024 Jun 17.
Artigo em Inglês | MEDLINE | ID: mdl-38884659

RESUMO

Effectively managing water resources in karst systems requires a thorough understanding of their general conduit network along with their seasonal dynamics. Their investigation has involved well construction or several advanced natural tracer data, most of which are not always available. Hence, this work showcases a pragmatic approach that makes use of basic hydrochemical variables of springs with coarse temporal resolution in characterising a karst system. In this study's example, physicochemical variables like major ion concentrations/ratios, Electrical Conductivity (EC), pH and water temperature (Tw) were measured on 20-day basis for a hydrological year at the Louros Catchment, Greece. We further performed the frequency distribution and variation analysis of EC and Tw, principal component analysis (PCA), scatter plots of carbonate ions vs sulphate and hydrochemographs to determine relevant hydrochemical processes and hydrogeological features. PCA and the scatter plots showed that the simple-type upper karst level is entirely dominated by carbonate dissolution, whereas the complex-type middle and lower levels also involve gypsum and dolomite dissolution. Presence of mixing between karst units was also detected. EC and Tw analyses revealed the degree of karstification of different units and relative depths of flow systems. Hydrochemographs reflected the seasonality of limestone and gypsum dissolution's contributions linked to the dominant flow type (conduit vs diffuse). This study thus was able to demonstrate the usefulness of such holistic hydrochemical analyses to better understand karst systems. Given their cost-effectiveness, they can be easily applied to any understudied karst system worldwide.


Assuntos
Monitoramento Ambiental , Grécia , Nascentes Naturais/química , Estações do Ano , Hidrologia , Movimentos da Água , Poluentes Químicos da Água/análise
6.
Sci Total Environ ; 941: 173671, 2024 Sep 01.
Artigo em Inglês | MEDLINE | ID: mdl-38825194

RESUMO

Polylepis trees grow at elevations above the continuous tree line (3000-5000 m a.s.l.) across the Andes. They tolerate extreme environmental conditions, making them sensitive bioindicators of global climate change. Therefore, investigating their ecohydrological role is key to understanding how the water cycle of Andean headwaters could be affected by predicted changes in environmental conditions, as well as ongoing Polylepis reforestation initiatives in the region. We estimate, for the first time, the annual water balance of a mature Polylepis forest (Polylepis reticulata) catchment (3780 m a.s.l.) located in the south Ecuadorian páramo using a unique set of field ecohydrological measurements including gross rainfall, throughfall, streamflow, and xylem sap flow in combination with the characterization of forest and soil features. We also compare the forest water balance with that of a tussock grass (Calamagrostis intermedia) catchment, the dominant páramo vegetation. Annual gross rainfall during the study period (April 2019-March 2020) was 1290.6 mm yr-1. Throughfall in the Polylepis forest represented 61.2 % of annual gross rainfall. Streamflow was the main component of the water balance of the forested site (59.6 %), while its change in soil water storage was negligible (<1 %). Forest evapotranspiration was 54.0 %, with evaporation from canopy interception (38.8 %) more than twice as high as transpiration (15.1 %). The error in the annual water balance of the Polylepis catchment was small (<15 %), providing confidence in the measurements and assumptions used to estimate its components. In comparison, streamflow and evapotranspiration at the grassland site accounted for 63.7 and 36.0 % of the water balance, respectively. Although evapotranspiration was larger in the forest catchment, its water yield was only marginally reduced (<4 %) in relation to the grassland catchment. The substantially higher soil organic matter content in the forest site (47.6 %) compared to the grassland site (31.8 %) suggests that even though Polylepis forests do not impair the hydrological function of high-Andean catchments, their presence contributes to carbon storage in the litter layer of the forest and the underlying soil. These findings provide key insights into the vegetation-water­carbon nexus in high Andean ecosystems, which can serve as a basis for future ecohydrological studies and improved management of páramo natural resources considering changes in land use and global climate.


Assuntos
Monitoramento Ambiental , Florestas , Equador , Clima Tropical , Hidrologia , Mudança Climática , Solo/química , Árvores , Altitude , Ciclo Hidrológico , Chuva , Água
7.
Environ Monit Assess ; 196(7): 608, 2024 Jun 11.
Artigo em Inglês | MEDLINE | ID: mdl-38861164

RESUMO

Satellite-based precipitation estimates are a critical source of information for understanding and predicting hydrological processes at regional or global scales. Given the potential variability in the accuracy and reliability of these estimates, comprehensive performance assessments are essential before their application in specific hydrological contexts. In this study, six satellite-based precipitation products (SPPs), namely, CHIRPS, CMORPH, GSMaP, IMERG, MSWEP, and PERSIANN, were evaluated for their utility in hydrological modeling, specifically in simulating streamflow using the Variable Infiltration Capacity (VIC) model. The performance of the VIC model under varying flow conditions and timescales was assessed using statistical indicators, viz., R2, KGE, PBias, RMSE, and RSR. The findings of the study demonstrate the effectiveness of VIC model in simulating hydrological components and its applicability in evaluating the accuracy and reliability of SPPs. The SPPs were shown to be valuable for streamflow simulation at monthly and daily timescales, as confirmed by various performance measures. Moreover, the performance of SPPs for simulating extreme flow events (streamflow above 75%, 90%, and 95%) using the VIC model was assessed and a significant decrease in the performance was observed for high-flow events. Comparative analysis revealed the superiority of IMERG and CMORPH for streamflow simulation at daily timescale and high-flow conditions. In contrast, the performances of CHIRPS and PERSIANN were found to be poor. This study highlights the importance of thoroughly assessing the SPPs in modeling diverse flow conditions.


Assuntos
Monitoramento Ambiental , Hidrologia , Chuva , Rios , Índia , Rios/química , Monitoramento Ambiental/métodos , Modelos Teóricos , Movimentos da Água , Imagens de Satélites , Clima Tropical
8.
Sci Total Environ ; 935: 173232, 2024 Jul 20.
Artigo em Inglês | MEDLINE | ID: mdl-38761926

RESUMO

Biogeochemical processes mediated by plants and soil in coastal marshes are vulnerable to environmental changes and biological invasion. In particular, tidal inundation and salinity stress will intensify under future rising sea level scenarios. In this study, the interactive effects of flooding regimes (non-waterlogging vs. waterlogging) and salinity (0, 5, 15, and 30 parts per thousand (ppt)) on photosynthetic carbon allocation in plant, rhizodeposition, and microbial communities in native (Phragmites australis) and invasive (Spartina alterniflora) marshes were investigated using mesocosm experiments and 13CO2 pulse-labeling techniques. The results showed that waterlogging and elevated salinity treatments decreased specific root allocation (SRA) of 13C, rhizodeposition allocation (RA) 13C, soil 13C content, grouped microbial PLFAs, and the fungal 13C proportion relative to total PLFAs-13C. The lowest SRA, RA, and fungal 13C proportion occurred under the combined waterlogging and high (30 ppt) salinity treatments. Relative to S. alterniflora, P. australis displayed greater sensitivity to hydrological changes, with a greater reduction in rhizodeposition, soil 13C content, and fungal PLFAs. S. alterniflora showed an earlier peak SRA but a lower root/shoot 13C ratio than P. australis. This suggests that S. alterniflora may transfer more photosynthetic carbon to the shoot and rhizosphere to facilitate invasion under stress. Waterlogging and high salinity treatments shifted C allocation towards bacteria over fungi for both plant species, with a higher allocation shift in S. alterniflora soil, revealing the species-specific microbial response to hydrological stresses. Potential shifts towards less efficient bacterial pathways might result in accelerated carbon loss. Over the study period, salinity was the primary driver for both species, explaining 33.2-50.8 % of 13C allocation in the plant-soil-microbe system. We propose that future carbon dynamics in coastal salt marshes under sea-level rise conditions depend on species-specific adaptive strategies and carbon allocation patterns of native and invasive plant-soil systems.


Assuntos
Espécies Introduzidas , Fotossíntese , Salinidade , Áreas Alagadas , Poaceae , Carbono/metabolismo , Hidrologia , Solo/química , Raízes de Plantas/metabolismo
9.
Sci Total Environ ; 931: 172925, 2024 Jun 25.
Artigo em Inglês | MEDLINE | ID: mdl-38697551

RESUMO

Subfossil pine and oak tree trunks were excavated during exploitation of the Budwity peatland in Northern Poland. Based on dendrochronological analysis, the woodland successions in peatland were reconstructed and correlated with moisture dynamics of the peatland ecosystem inferred from the high-resolution multi-proxy analysis of the peatland deposits. From the results of dendrochronological analysis and the 14C wiggle matching methods, four floating pine chronologies (5882-5595; 5250-5089; 3702-3546; and 2222-1979 mod. cal BP) and two oak chronologies (4932-4599 and 4042-3726 mod. cal BP) were developed. The organic sediments of the peatland (6 m thick) were deposited over approximately nine thousand years. The lower complex (525-315 cm) comprises minerogenic peat, while the upper complex (315.0-0.0 cm) is composed of ombrogenic peat. Subfossil tree trunks are distributed across various peat horizons, which suggests multiple stages of tree colonisation followed by subsequent dying-off phases. Multiproxy sediment analyses (lithological, geochemical and δ13C stable isotope, pollen, plant macrofossils, Cladocera, diatom, and Diptera analyses) indicate that the two earliest phases of pine colonisation (5882-5595 and 5250-5089 mod. cal BP) and the two stages of oak colonisation (4932-4599 and 4042-3726 mod. cal BP) were associated with periodic drying of the peatland. Conversely, tree dying-off phases occurred during periods of increased water levels in the peatland, coinciding with stages of increasing climate humidity during the Holocene. The two most recent phases of pine colonisation occurred during the ombrogenic stage of mire development. Remnants of the dead forest from these phases, marked by subfossil trunks still rooted in the ground, were preserved and exposed presently during peat exploitation, approximately 2.5 m below ground level. The identified phases of tree colonisation and subsequent dying-off phases show correlation with analogical phenomena observed in the other investigated European peatlands.


Assuntos
Pinus , Quercus , Solo , Áreas Alagadas , Polônia , Solo/química , Monitoramento Ambiental , Hidrologia , Ecossistema , Sedimentos Geológicos/química
10.
J Environ Manage ; 359: 121018, 2024 May.
Artigo em Inglês | MEDLINE | ID: mdl-38714033

RESUMO

The estimation and prediction of the amount of sediment accumulated in reservoirs are imperative for sustainable reservoir sedimentation planning and management and to minimize reservoir storage capacity loss. The main objective of this study was to estimate and predict reservoir sedimentation using multilayer perceptron-artificial neural network (MLP-ANN) and random forest regressor (RFR) models in the Gibe-III reservoir, Omo-Gibe River basin. The hydrological and meteorological parameters considered for the estimation and prediction of reservoir sedimentation include annual rainfall, annual water inflow, minimum reservoir level, and reservoir storage capacity. The MLP-ANN and RFR models were employed to estimate and predict the amount of sediment accumulated in the Gibe-III reservoir using time series data from 2014 to 2022. ANN-architecture N4-100-100-1 with a coefficient of determination (R2) of 0.97 for the (80, 20) train-test approach was chosen because it showed better performance both in training and testing (validation) the model. The MLP-ANN and RFR models' performance evaluation was conducted using MAE, MSE, RMSE, and R2. The models' evaluation result revealed that the MLP-ANN model outperformed the RFR model. Regarding the train data simulation of MLP-ANN and RFR shown R2 (0.99) and RMSE (0.77); and R2 (0.97) and RMSE (1.80), respectively. On the other hand, the test data simulation of MLP-ANN and RFR demonstrated R2 (0.98) and RMSE (1.32); and R2 (0.96) and RMSE (2.64), respectively. The MLP-ANN model simulation output indicates that the amount of sediment accumulation in the Gibe-III reservoir will increase in the future, reaching 110 MT in 2030-2031, 130 MT in 2050-2051, and above 137 MTin 2071-2072.


Assuntos
Redes Neurais de Computação , Rios , Etiópia , Rios/química , Sedimentos Geológicos/análise , Hidrologia , Modelos Teóricos , Monitoramento Ambiental/métodos
11.
J Environ Manage ; 359: 121044, 2024 May.
Artigo em Inglês | MEDLINE | ID: mdl-38714035

RESUMO

Dams and reservoirs have significantly altered river flow dynamics worldwide. Accurately representing reservoir operations in hydrological models is crucial yet challenging. Detailed reservoir operation data is often inaccessible, leading to relying on simplified reservoir operation modules in most hydrological models. To improve the capability of hydrological models to capture flow variability influenced by reservoirs, this study proposes a hybrid hydrological modeling framework, which combines a process-based hydrological model with a machine-learning-based reservoir operation module designed to simulate runoff under reservoir operations. The reservoir operation module employs an ensemble of three machine learning models: random forest, support vector machine, and AutoGluon. These models predict reservoir outflows using precipitation and temperature data as inputs. The Soil and Water Assessment Tool (SWAT) then integrates these outflow predictions to simulate runoff. To evaluate the performance of this hybrid approach, the Xijiang Basin within the Pearl River Basin, China, is used as a case study. The results highlight the superiority of the SWAT model coupled with machine learning-based reservoir operation models compared to alternative modeling approaches. This hybrid model effectively captures peak flows and dry period runoff. The Nash-Sutcliffe Efficiency (NSE) in daily runoff simulations shows substantial improvement, ranging from 0.141 to 0.780, with corresponding enhancements in the coefficient of determination (R2) by 0.098-0.397 when compared to the original reservoir operation modules in SWAT. In comparison to parameterization techniques lacking a dedicated reservoir module, NSE enhancements range from 0.068 to 0.537, and R2 improvements range from 0.027 to 0.139. The proposed hybrid modeling approach effectively characterizes the impact of reservoir operations on river flow dynamics, leading to enhanced accuracy in runoff simulation. These findings offer valuable insights for hydrological forecasting and water resources management in regions influenced by reservoir operations.


Assuntos
Hidrologia , Aprendizado de Máquina , Modelos Teóricos , Rios , Humanos , China , Movimentos da Água
12.
J Environ Manage ; 359: 121082, 2024 May.
Artigo em Inglês | MEDLINE | ID: mdl-38728985

RESUMO

Rainfall is a key hydro meteorological variable. Climate change is disrupting the hydrological cycle and altering the usual cycle of rainfall, which frequently results in long-lasting storms with significant rainfall. A first step in hydrologic design of project is to determine the design storm or rainfall events to be used. For deriving design storm, researchers concluded that instead of using generalized readily available curves or maps, it is better to estimate design storm based on site specific historical rainfall data. The objective of the study is to analyze the rainfall data in the koyna watershed area in order to evaluate the design storm, which will be further used as an input data for HEC-HMS event based hydrological modelling of flood peak attenuation of design storm flow at koyna dam during extreme rainfall event. In this study, 40 years (1982-2021) of rainfall data from 8 rain gauge stations in Koyna Dam Catchment area is used initially for performing trend analysis through statistical and graphical techniques and then for Isopluvial analysis. The Sen's slope test and the Mann-Kendall test are the statistical techniques employed, and Innovative Trend Analysis is the graphical technique used. IDF approach is used for deriving design storm, and using Gumbel's frequency distribution method Isohyetal maps, IDF tables and curves are prepared for 2,10,25,50,75 and 100 year return periods and 6,12,24,48 and 96 h durations. Results obtained from statistical and graphical trend analysis of annual rainfall series are consistent. No statistically significant trend in annual rainfall series is observed, however there is rising and falling trend was observed in annual as well as monthly rainfall series. From the results of design storm study, the design storm hyetograph of 10 years return period and 96 h duration is selected, which gives the rainfall intensity of 10.88 mm/h for the koyna catchment. There are various dams nearby koyna catchment, The Isohyet maps, IDF curves and table output available from this study can be more reliably used during planning and design of hydraulic structure for other areas near by koyna catchment.


Assuntos
Hidrologia , Chuva , Índia , Mudança Climática , Modelos Teóricos , Inundações
13.
Sci Total Environ ; 934: 173198, 2024 Jul 15.
Artigo em Inglês | MEDLINE | ID: mdl-38750740

RESUMO

Land use and climate changes are driving significant shifts in the magnitude and persistence of dryland stream surface flows. The impact of these shifts on ecological functioning is largely unknown, particularly where streams have become wetter rather than drier. This study investigated relationships between hydrologic regime (including surface water persistence, differences in groundwater depth and altered flooding dynamics) with plant traits and riverine vegetation functional composition. Our study system was a previously ephemeral creek in semi-arid northwest Australia that has received groundwater discharge from nearby mining operations for >15 years; surface flows are now persistent for ∼27 km downstream of the discharge point. We aimed to (i) identify plant functional groups (FGs) associated with the creek and adjacent floodplain; and (ii) assess their distribution across hydrological gradients to predict shifts in ecological functioning in response to changing flow regimes. Seven FGs were identified using hierarchical clustering of 40 woody perennial plant species based on morphometric, phenological and physiologic traits. We then investigated how FG abundance (projective foliar cover), functional composition, and functional and taxonomic richness varied along a 14 km gradient from persistent to ephemeral flows, varying groundwater depths, and distances from the stream channel. Dominant FGs were (i) drought avoidant mesic trees that are fluvial stress tolerant, or (ii) drought tolerant xeric tall shrubs that are fluvial stress intolerant. The drought avoidant mesic tree FG was associated with shallow groundwater but exhibited lower cover in riparian areas closer to the discharge (persistent surface flows). However, there were more FGs and higher species richness closer to the discharge point, particularly on the floodplain. Our findings demonstrate that quantifying FG distribution and diversity is a significant step in both assessing the impacts of mine water discharge on riverine ecosystems and for planning for post-mining restoration.


Assuntos
Rios , Biodiversidade , Monitoramento Ambiental/métodos , Plantas , Movimentos da Água , Mudança Climática , Ecossistema , Territórios do Noroeste , Hidrologia , Água Subterrânea
14.
Sci Total Environ ; 940: 173480, 2024 Aug 25.
Artigo em Inglês | MEDLINE | ID: mdl-38796012

RESUMO

The rewetting of formerly drained peatlands can help to counteract climate change through the reduction of CO2 emissions. However, this can lead to resuming CH4 emissions due to changes in the microbiome, favoring CH4-producing archaea. How plants, hydrology and microbiomes interact as ultimate determinants of CH4 dynamics is still poorly understood. Using a mesocosm approach, we studied peat microbiomes, below-ground root biomass and CH4 fluxes with three different water level regimes (stable high, stable low and fluctuating) and four different plant communities (bare peat, Carex rostrata, Juncus inflexus and their mixture) over the course of one growing season. A significant difference in microbiome composition was found between mesocosms with and without plants, while the difference between plant species identity or water regimes was rather weak. A significant difference was also found between the upper and lower peat, with the difference increasing as plants grew. By the end of the growing season, the methanogen relative abundance was higher in the sub-soil layer, as well as in the bare peat and C. rostrata pots, as compared to J. inflexus or mixture pots. This was inversely linked to the larger root area of J. inflexus. The root area also negatively correlated with CH4 fluxes which positively correlated with the relative abundance of methanogens. Despite the absence or low abundance of methanotrophs in many samples, the integration of methanotroph abundance improved the quality of the correlation with CH4 fluxes, and methanogens and methanotrophs together determined CH4 fluxes in a structural equation model. However, water regime showed no significant impact on plant roots and methanogens, and consequently, on CH4 fluxes. This study showed that plant roots determined the microbiome composition and, in particular, the relative abundance of methanogens and methanotrophs, which, in interaction, drove the CH4 fluxes.


Assuntos
Metano , Microbiota , Raízes de Plantas , Metano/metabolismo , Raízes de Plantas/microbiologia , Áreas Alagadas , Hidrologia , Microbiologia do Solo
15.
Science ; 384(6696): 697-703, 2024 May 10.
Artigo em Inglês | MEDLINE | ID: mdl-38723080

RESUMO

Changes in climate shift the geographic locations that are suitable for malaria transmission because of the thermal constraints on vector Anopheles mosquitos and Plasmodium spp. malaria parasites and the lack of availability of surface water for vector breeding. Previous Africa-wide assessments have tended to solely represent surface water using precipitation, ignoring many important hydrological processes. Here, we applied a validated and weighted ensemble of global hydrological and climate models to estimate present and future areas of hydroclimatic suitability for malaria transmission. With explicit surface water representation, we predict a net decrease in areas suitable for malaria transmission from 2025 onward, greater sensitivity to future greenhouse gas emissions, and different, more complex, malaria transmission patterns. Areas of malaria transmission that are projected to change are smaller than those estimated by precipitation-based estimates but are associated with greater changes in transmission season lengths.


Assuntos
Anopheles , Mudança Climática , Hidrologia , Malária , Mosquitos Vetores , Água , Animais , Humanos , África/epidemiologia , Anopheles/parasitologia , Gases de Efeito Estufa/análise , Malária/transmissão , Mosquitos Vetores/parasitologia , Chuva , Estações do Ano , Água/parasitologia , Plasmodium , Modelos Epidemiológicos
16.
Environ Sci Technol ; 58(22): 9701-9713, 2024 Jun 04.
Artigo em Inglês | MEDLINE | ID: mdl-38780660

RESUMO

Indirect nitrous oxide (N2O) emissions from streams and rivers are a poorly constrained term in the global N2O budget. Current models of riverine N2O emissions place a strong focus on denitrification in groundwater and riverine environments as a dominant source of riverine N2O, but do not explicitly consider direct N2O input from terrestrial ecosystems. Here, we combine N2O isotope measurements and spatial stream network modeling to show that terrestrial-aquatic interactions, driven by changing hydrologic connectivity, control the sources and dynamics of riverine N2O in a mesoscale river network within the U.S. Corn Belt. We find that N2O produced from nitrification constituted a substantial fraction (i.e., >30%) of riverine N2O across the entire river network. The delivery of soil-produced N2O to streams was identified as a key mechanism for the high nitrification contribution and potentially accounted for more than 40% of the total riverine emission. This revealed large terrestrial N2O input implies an important climate-N2O feedback mechanism that may enhance riverine N2O emissions under a wetter and warmer climate. Inadequate representation of hydrologic connectivity in observations and modeling of riverine N2O emissions may result in significant underestimations.


Assuntos
Hidrologia , Óxido Nitroso , Rios , Rios/química , Água Subterrânea/química , Ecossistema , Nitrificação , Solo/química , Monitoramento Ambiental
17.
J Environ Manage ; 360: 121137, 2024 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-38796874

RESUMO

Understanding the relationship between hydrological connectivity (HC) and water level (WL) is crucial for effective water resource management and wetland restoration. However, current knowledge regarding this relationship is limited. This study proposed an integrated nonstationary and uncertain analysis framework (INUAF) to investigate the HC-WL relationship with reference to the Baiyangdian wetland, which is a fragmented wetland in North China. With the INUAF, the interannual and intra-annual variations of both HC and WL were examined, together with the wavelet coherence and lag effects between the two variables at multiple scales. The results highlighted marked nonstationarity in HC, WL, and the relationship between them. Scale-dependent lag effects revealed that HC lags WL by 37 days (131 days) at the 1 a scale (4 a scale), and leads WL by 190 days at the 8 a scale, indicating a complex coupled relationship between HC and WL. Additionally, the INUAF was applied to evaluating the uncertainty in the response of lagged HC to varied WL. Results indicated that every 0.2-m increase in WL led to a 2.2%-2.4% higher probability of maintaining high HC for WL between 6.0 and 8.0 m, but a 10%-11% higher probability for WL between 8.0 and 9.0 m. We suggest that a WL of > 8.4 m would produce a probability of > 50% for achieving high HC. These findings provide valuable insights into the HC-WL relationship and could contribute to wetland restoration efforts.


Assuntos
Hidrologia , Áreas Alagadas , China , Incerteza , Água
18.
Environ Sci Pollut Res Int ; 31(27): 39098-39119, 2024 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-38811456

RESUMO

Physically based or data-driven models can be used for understanding basinwide hydrological processes and creating predictions for future conditions. Physically based models use physical laws and principles to represent hydrological processes. In contrast, data-driven models focus on input-output relationships. Although both approaches have found applications in hydrology, studies that compare these approaches are still limited for data-scarce, semi-arid basins with altered hydrological regimes. This study aims to compare the performances of a physically based model (Soil and Water Assessment Tool (SWAT)) and a data-driven model (Nonlinear AutoRegressive eXogenous model (NARX)) for reservoir volume and streamflow prediction in a data-scarce semi-arid region. The study was conducted in the Tersakan Basin, a semi-arid agricultural basin in Türkiye, where the basin hydrology was significantly altered due to reservoirs (Ladik and Yedikir Reservoir) constructed for irrigation purposes. The models were calibrated and validated for streamflow and reservoir volumes. The results show that (1) NARX performed better in the prediction of water volumes of Ladik and Yedikir Reservoirs and streamflow at the basin outlet than SWAT (2). The SWAT and NARX models both provided the best performance when predicting water volumes at the Ladik reservoir. Both models provided the second best performance during the prediction of water volumes at the Yedikir reservoir. The model performances were the lowest for prediction of streamflow at the basin outlet (3). Comparison of physically based and data-driven models is challenging due to their different characteristics and input data requirements. In this study, the data-driven model provided higher performance than the physically based model. However, input data used for establishing the physically based model had several uncertainties, which may be responsible for the lower performance. Data-driven models can provide alternatives to physically-based models under data-scarce conditions.


Assuntos
Hidrologia , Modelos Teóricos , Rios/química , Movimentos da Água , Agricultura
19.
Sci Total Environ ; 935: 173369, 2024 Jul 20.
Artigo em Inglês | MEDLINE | ID: mdl-38777071

RESUMO

Green infrastructure (GI), as one type of ecological stormwater management practices, can potentially alleviate water problems and deliver a wide range of environmental benefits in urban areas. GIs are often planned and designed to reduce runoff and mitigate pollution. However, the influence of GI on groundwater hydrology and that of shallow groundwater on GI performance was seldom considered. This study utilized a calibrated surface-subsurface hydrological model, i.e., Storm Water Management Model coupled with USGS's modular hydrologic model (SWMM-MODFLOW) to consider the interaction between GI and groundwater into the process of GI planning. The optimal implementation ratio, aggregation level and upstream-downstream location of bioretention cells (BC, one type of GI) under different planning objectives and hydrogeologic conditions was explored. The consideration of groundwater management exerted a significant impact on the optimal spatial allocation of BCs. The results showed that when groundwater management was more concerned than runoff control, BCs were recommended to be allocated more apart from each other and more upstream in the catchment because more-distributed and upstream BCs can result in lower groundwater table rise which is beneficial. BCs were overall recommended to be allocated in areas of deeper groundwater tables, coarser soils, and flatter topographies. However, the spatial features of BCs are related to each other, the choice of them are affected by various hydrogeologic factors simultaneously. The exact location of BCs should be determined by considering the trade-off between runoff control efficiency and groundwater impact. The findings obtained in this study can provide guidance on GI planning in shallow groundwater areas.


Assuntos
Água Subterrânea , Água Subterrânea/química , Hidrologia , Modelos Teóricos , Monitoramento Ambiental , Movimentos da Água
20.
J Environ Manage ; 360: 121119, 2024 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-38733849

RESUMO

Soil property data plays a crucial role in watershed hydrology and non-point source (H/NPS) modeling, but how to improve modeling accuracy with affordable soil samplings and the effects of sampling information on H/NPS modeling remains to be further explored. In this study, the number of sampling points and soil properties were optimized by the information entropy and the spatial interpolation method. Then the sampled properties were parameterized and the effects of different parameterization schemes on H/NPS modeling were tested using the Soil and Water Assessment Tool (SWAT). The results indicated that the required sampling points increased successively for soil bulk density (SOL_BD), soil saturated hydraulic conductivity (SOL_K) and soil available water capacity (SOL_AWC). Compared to the traditional database (Harmonized world soil database), the NSE and R2 performance by new scheme increased by 22.8% and 10.5%, respectively. The entropy-based optimization reduced the sampling points by 13.2%, indicating a more cost-effective scheme. Compared to hydrological simulation, sampled properties showed greater effects on NPS modeling, especially for nitrogen. This proposed method/framework can be generalized to other watersheds by upscaling field soil sampling information to the watershed scale, thus improving H/NPS simulation.


Assuntos
Entropia , Hidrologia , Solo , Modelos Teóricos , Água , Monitoramento Ambiental/métodos
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