Haw Yen

Wet dissolved carbon deposition is a critical node of the global carbon cycle, but little is known about dissolved organic and inorganic carbon (DOC and DIC) concentrations and fluxes in the semi-arid areas of the Loess Plateau Region (LPR). In this study, we measured variations of DOC and DIC concentration in rainfalls at Yangjuangou Ecological Restoration and Soil and Water Observatory. Rainwater samples were collected in 16 rainfall events from July to September and the event-based, monthly concentrations and fluxes of DOC and DIC were quantified. The results showed that the event-based concentrations and fluxes of DOC and DIC were highly variable, ranging from 0.56 to 28.71 mg C L⁻¹ and from 3.47 to 17.49 mg C L⁻¹, respectively. The corresponding event-based fluxes ranged from 0.21-258.36 mg C m⁻² and from 4.12 to 42.32 mg C m⁻². The monthly concentrations of DOC and DIC were 24.62 and 4.30 (July), 3.58 and 10.52 (August), 1.01 and 5.89 (September) mg C L⁻¹, respectively. Thus, the monthly deposition fluxes of DOC and DIC were 541.64/94.60, 131.03/385.03, and 44.44/259.16 mg C m⁻² for July, August and September, respectively. In addition, the concentrations of DOC and DIC for the concentrated rainfall season (July-September) in the studied catchment were 7.06 and 7.00 mg C L⁻¹, respectively. The estimated annual wet dissolved carbon depositions were 1.91 and 1.89 g C m⁻² yr⁻¹ for DOC and DIC, respectively. The results of this study suggest the variation in concentrations and fluxes of DOC and DIC and explored that these variation may be related to the dissolved carbon source and the rainfall characteristics during the concentrated rainfall season in the semi-arid catchment of the LPR. Furthermore, these results also suggest that dissolved carbon may be an important external input of carbon into terrestrial ecosystems.

<p>Farm ponds, which are sometimes numerous and widely distributed in agricultural regions, have faced widespread degradation in recent decades. Although relevant conservation strategies have gradually increased, detailed assessments on their roles in regional biogeochemistry and ecology are lacking. We concluded that farm ponds provided hydrologic, biogeochemical, and socioeconomic benefits to southern China for thousands of years, but they are facing contemporary threats and management challenges, including (1) inadequate planning in terms of construction and conservation regulations; (2) rural nonpoint source and mini-point source pollution; (3) climate change-induced abnormalities in the hydroperiod and disturbance to wildlife; (4) invasive species; and (5) inadequate social and political capacity to consider ecological conservation. As farm ponds function as wetland complexes that are embedded within or integral to larger ecosystems, we recommend multi-disciplinary efforts over scales ranging from within-pond to regional for their assessment and conservation.</p><p>Excessive nitrogen (N) discharge from agriculture is a major factor of widespread problems in aquatic ecosystems. Knowledge of spatiotemporal patterns and source attribution of N pollution in these small, scattered ponds is a critical first step for nutrient management and ecosystem health in low-order agricultural watersheds. We applied the process-based HSPF model for ponds, ditches, and downstream waters in a 4.8 km<sup>2</sup> test watershed in southern China. The results exhibited distinctive spatial-seasonal variations with an overall seriousness rank for the three indicators: total nitrogen (TN) > nitrate/nitrite nitrogen (NO<sub>x</sub><sup>-</sup>-N) > ammonia nitrogen (NH<sub>3</sub>-N). TN pollution was severe for the entire watershed, while NO<sub>x</sub><sup>-</sup>-N pollution was significant for ponds and ditches far from the village, and the NH<sub>3</sub>-N concentrations were acceptable except for the ponds near the village in summer. Although food and cash crop production accounted for the largest source of N loads, we discovered that mini-point pollution sources, including animal feeding operations, rural residential sewage, and waste, together contributed as high as 47% of the TN and NH<sub>3</sub>-N loads in ponds and ditches.</p><p>Our synthetic analysis and process-based modeling studies focused on farm ponds in an agriculturally dominated developing country (China), but similar small, scattered wetlands and their degradation trends are observed worldwide (e.g., vernal pools and prairie potholes in North American, farm ponds in Western and Central Europe, and chain of natural pond system in Australia). Nature-based solutions are becoming increasingly recognized as important for addressing the complex challenges in hydrology, ecology, and biodiversity under anthropogenic and climatic pressures. Apart from proposed conservation policies, including public awareness building, top-down regulations and bottom-up engagement, and sustainable management and utilization, we are also trying techniques that involve interconnected smart sensors and integrated modeling methods to better understand pond hydrological processes. We believe that such solutions can provide a basis for the numerical assessments on their ecosystem services and associated conservation cost analyses.</p>

Organophosphate esters (OPEs) pose increasing concerns for their widespread distribution in soil environments and potential threat to human health. In this study, we investigated the occurrence and associated risks of seven OPEs in surface soils and the potential influence of human activities on soil OPE contamination in a heavily urbanized region of the Yangtze River Delta in Eastern China. All target OPEs were detected in the soil samples (100% of samples) reflecting their widespread distribution in the study region. The total OPE concentration (the sum of the seven OPEs) ranged from 162.7 to 986.0 ng/g on a dry weight basis, with a mean value of 469.3 ± 178.6 ng/g. Tris (2-butoxyethyl) phosphate was the main compound, accounting for 67-78% of the total OPE concentration. Ecological risk assessment showed that tris(2-chloroisopropyl) phosphate, tris(2,3-dichloropropyl) phosphate, tris(2-butoxyethyl) phosphate, and tris(2-ethylhexyl) phosphate posed a medium potential risk to terrestrial biota (0.1 < risk quotient <1). The human exposure estimation showed insignificant risks to local population. Redundancy analysis revealed that the individual and total OPE contaminations were positively correlated with human activity parameters. The total OPE concentrations were positively correlated to population density (R2 = 0.38, P < 0.001), and urban land use percentage (R2 = 0.39, P < 0.001), while negatively correlated to forest land use percentage (R2 = 0.59, P < 0.001), suggesting a significant contribution of human disturbance to OPE pollution. These results can facilitate OPE contamination control and promote sustainable soil management in urbanized and industrialized regions.

In response to degraded water quality, federal policy makers in the US and Canada called for a 40% reduction in phosphorus (P) loads to Lake Erie, and state and provincial policy makers in the Great Lakes region set a load‐reduction target for the year 2025. Here, we configured five separate SWAT (US Department of Agriculture's Soil and Water Assessment Tool) models to assess load reduction strategies for the agriculturally dominated Maumee River watershed, the largest P source contributing to toxic algal blooms in Lake Erie. Although several potential pathways may achieve the target loads, our results show that any successful pathway will require large‐scale implementation of multiple practices. For example, one successful pathway involved targeting 50% of row cropland that has the highest P loss in the watershed with a combination of three practices: subsurface application of P fertilizers, planting cereal rye as a winter cover crop, and installing buffer strips. Achieving the...

Nitrogen (N) losses through runoff from cropland and atmospheric deposition contributed by agricultural NH3 volatilization are important contributors to lake eutrophication and receive wide attention. Studies on the N runoff and atmospheric N deposition from the paddy ecosystem and how the agriculture-derived N deposition was related to NH3 volatilization were conducted in the paddy ecosystem in the Erhai Lake Watershed in southwest China. The critical period (CP) with a relatively high total N (TN) and NH4+-N deposition occurred in the fertilization period and continued one week after the completion of fertilizer application, and the CP period for N loss through surface runoff was one week longer than that for deposition. Especially, the mean depositions of NH4+-N in the CP period were substantially higher than those in the subsequent period (p < 0.01). Moreover, agriculture-derived NH4+ contributed more than 54% of the total NH4+-N deposition in the CP period, being positively ...

For surface runoff estimation in the Soil and Water Assessment Tool (SWAT) model, the curve number (CN) procedure is commonly adopted to calculate surface runoff by dynamically updating CN values based on antecedent soil moisture condition (SCSI) in field. From SWAT2005 and onward, an alternative approach has become available to apply the CN method by relating the runoff potential to daily evapotranspiration (SCSII). While improved runoff prediction with SCSII has been reported in several case studies, few investigations have been made on its influence to water quality output or on the model uncertainty associated with the SCSII method. The objectives of the research were: (1) to quantify the improvements in hydrologic and water quality predictions obtained through different surface runoff estimation techniques; and (2) to examine how model uncertainty is affected by combining different surface runoff estimation techniques within SWAT using Bayesian model averaging (BMA). Applicatio...

Integrated water quantity and quality simulations have become a popular tool in investigations on global water crisis. For integrated and complex models, conventional uncertainty estimations focus on the uncertainties of individual modules, e.g., module parameters and structures, and do not consider the uncertainties propagated from interconnected modules. Therefore, this study investigated all the uncertainties of integrated water system simulations using the GLUE (i.e., generalized likelihood uncertainty estimation) method, including uncertainties associated with individual modules, propagated uncertainties associated with interconnected modules, and their combinations. The changes in both acceptability thresholds of GLUE and the uncertainty estimation results were also investigated for different fixed percentages of total number of iterations (100000). Water quantity and quality variables (i.e., runoff and ammonium nitrogen) were selected for the case study. The results showed th...

In the past three decades, sophisticated watershed simulation models are developed to conduct hydrological and nutrient processes to evaluate relevant environmental issues and challenges. In previous studies, it has been shown that the incorporation of input uncertainty by latent variables may enhance the performance of model predictions. In addition, the associated predictive uncertainty can be reduced. In this study, the Integrated Parameter Estimation and Uncertainty Analysis Tool (IPEAT) is incorporated with the Soil and Water Assessment Tool (SWAT) to explore the impact towards model predictions by altering default ranges of latent variables. The results suggested that the inclusion of input uncertainty by using latent variables may not guarantee the enhanced performance of model predictions nor the predictive uncertainty can be reduced. It may not be appropriate to use latent variables to incorporate input uncertainty during the auto-calibration process.

Large scale hydrologic systems include complex interactions and recursions among different physical processes. To duplicate real world phenomenon, sophisticated simulation models usually enclose large number of parameter sets and the calibration process can be extremely difficult. Up to date, Bayes' theory has been widely adopted to develop efficient parameter searching techniques. In this study, three Bayesian approaches are introduced: the Metropolis- Hastings Algorithm (MHA), the Gibbs Sampling algorithm (GSA) and the Uniform Covering by Probabilistic Rejection (UCPR). The MHA and the GSA are classical MCMC applications which can be largely found in literatures from different fields. The UCPR is a special version of Bayesian approach which is capable in managing prior information to explore model parameters without having computational intensive model evaluations. Beyond Bayesian approaches, two other global optimization algorithms: Dynamically Dimensioned Search (DDS) and Sh...

Watershed-scale hydrological models have become important tools to understand, assess, and predict the impacts of natural and anthropogenic-driven activities on water resources. However, model predictions are associated with uncertainties stemming from sources such as model input data. As an important input to most watershed models, land use/cover (LULC) data can affect hydrological predictions and influence the interpretation of modeling results. In addition, it has been shown that the use of soft data will further ensure the quality of modeling results to be closer to watershed behavior. In this study, the ecologically relevant flows (ERFs) are the primary soft data to be considered as a part of the modeling processes. This study aims to evaluate the impacts of LULC input data on the hydrological responses of the rapidly urbanizing Upper Cahaba River watershed (UCRW) located in Alabama, USA. Two sources of LULC data, i.e., National Land Cover Database (NLCD) and Digitized Landsat ...

Erosion-induced soil carbon loss has been identified as a critical process in the global carbon (C) cycle. Surface coverage substantially alters the soil erosion process and the effects of net loss or deposition on soil organic C (SOC). However, information on SOC loss induced by soil erosion at the process level is limited. The aim of this study was to investigate how runoff and erosion regimes affect dissolved and sediment-bound organic C (DOC and SBOC) loss. Thus, six simulated rainfall events were conducted on two laboratory plots (9.75 m × 1.83 m) with different surface coverages (17-83%) and coverage distributions (upslope vs. downslope) using polypropylene geotextiles. The results showed that the variability in the process of runoff and sediment yield existed as a result of altered surface coverage over the erosion zone (SSerosion zone) and covered zone (SScovered zone) on the slope. Thus, the erosion regimes can be identified as deposition- and transport-dominated processes, which were the main soil erosion subprocesses. The surface coverage located downslope (SCtop-bottom slope) can more efficiently reduce runoff (21.9-85.7%) and sediment (67.6-98.3%) than the SCbottom-top slope (runoff: 20.1-83.0%; sediment: 35.0-93.3%), which has the surface coverage located upslope. DOC (8.0-11.3 mg L-1) and SBOC (0.3-0.5 mg g-1) in the deposition-dominated process on the SCtop-bottom slope were higher than in the transport-dominated process on the SCbottom-top slope (DOC: 6.8-10.2 mg L-1; SBOC: 0.2-0.3 mg g-1). The loading of DOC and SBOC was largely dependent on runoff and sediment yield, and DOC load contributed 83.9-89.7% of the SOC loss. Overall, laboratory results highlighted the soil C loss at different hydrological and erosion regimes (deposition- vs. transport-dominated process). This study provides important information that can be used to facilitate further implementations such as watershed modeling of soil C dynamics and the corresponding decision-making processes.

Temporal scale is an important keyword in environmental hydrology but little information is available in the relationship between correlation and time variability degree of hydro-environmental variables at a watershed scale, which makes it difficult to design effective real-time management strategies. Here we take the Yanhe River Watershed as a study case to simulate and inventory the fractal characteristics of correlation and time variability degree of runoff, rainfall, and NH4+-N at different time scales, focusing on the long-term series of 1984-2012. (i) The coupled modeling framework based on SWAT (Soil and Water Assessment Tool), statistics and fractal theory is a time series analysis method that is particularly suitable for the evaluation of long-range correlation of non-linear time series. The Nash-Sutcliffe Efficiency coefficient (NSE), R2 and PBIAS during the calibration and verification period proved the reliability and acceptability of the established SWAT model in modeling multi-time scale runoff and NH4+-N load in the upstream catchment of Ganguyi hydrological station. (ii) Runoffs at all time scales showed positive correlations with rainfall although the significant level had a certain time scale differences. More interestingly, the correlation between NH4+-N loss and runoff at different time scales was significantly higher than that of rainfall. (iii) Each hydro-environmental variable has different fractal and time variation characteristics at different time scales, and the correlation levels between different hydrological variables are not completely consistent with their own time variability degrees at different time scales. These findings point to a fundamental challenge in managing regions with leading infiltration-excess runoff and uneven nutrient loading because the meteorological and hydrological variables in these regions exhibit the strongest temporal variability, which will affect the effective allocation and implementation in management practices.

For almost 30 years, the Soil and Water Assessment Tool (SWAT) has been successfully implemented to address issues around various scientific subjects in the world. On the other hand, it has been reaching to the limit of potential flexibility in further development by the current structure. The new generation SWAT, dubbed SWAT+, was released recently with entirely new coding features. SWAT+ is designed to have far more advanced functions and capacities to handle challenging watershed modeling tasks for hydrologic and water quality processes. However, it is still inevitable to conduct model calibration before the SWAT+ model is applied to engineering projects and research programs. The primary goal of this study is to develop an open-source, easy-to-operate automatic calibration tool for SWAT+, dubbed IPEAT+ (Integrated Parameter Estimation and Uncertainty Analysis Tool Plus). There are four major advantages: (i) Open-source code to general users; (ii) compiled and integrated directly...