Abstract. Watershed-scale modeling can be a valuable tool to aid in quantification of water quality and yield; however, several challenges remain. In many watersheds, it is difficult to adequately quantify hydrologic partitioning. Data scarcity is prevalent, accuracy of spatially distributed meteorology is difficult to quantify, forest encroachment and land use issues are common, and surface water and groundwater abstractions substantially modify watershed-based processes. Our objective is to assess the capability of the Soil and Water Assessment Tool (SWAT) model to capture eventbased and long-term monsoonal rainfall-runoff processes in complex mountainous terrain. To accomplish this, we developed a unique quality-control, gap-filling algorithm for interpolation of high-frequency meteorological data. We used a novel multi-location, multi-optimization calibration technique to improve estimations of catchment-wide hydrologic partitioning. The interdisciplinary model was calibrated to a unique combination of statistical, hydrologic, and plant growth metrics. Our results indicate scale-dependent sensitivity of hydrologic partitioning and substantial influence of engineered features. The addition of hydrologic and plant growth objective functions identified the importance of culverts in catchment-wide flow distribution. While this study shows the challenges of applying the SWAT model to complex terrain and extreme environments; by incorporating anthropogenic features into modeling scenarios, we can enhance our understanding of the hydroecological impact.
Peatlands perform important ecosystem functions, such as carbon storage and nutrient retention, which are affected, among other factors, by vegetation and peat decomposition. The availability of silicon (Si) in peatlands differs strongly, ranging from <1 to >25 mg L−1. Since decomposition of organic material was recently shown to be accelerated by Si, the aim of this study was to examine how Si influences decomposition of carbon and nutrient and toxicant mobilization in peatlands. We selected a fen site in Northern Bavaria with naturally bioavailable Si pore water concentrations of 5 mg/L and conducted a Si addition experiment. At a fourfold higher Si availability, dissolved organic carbon, carbon dioxide, and methane concentrations increased significantly. Furthermore, dissolved nitrogen, phosphorus, iron, manganese, cobalt, zinc, and arsenic concentrations were significantly higher under high Si availability. This enhanced mobilization may result from Si competing for binding sites but also from stronger reducing conditions, caused by accelerated respiration. The stronger reducing conditions also increased reduction of arsenate to arsenite and thus the mobility of this toxicant. Hence, higher Si availability is suggested to decrease carbon storage and increase nutrient and toxicant mobility in peatland ecosystems.
Abstract:In this paper, we present the Daily based Morgan-Morgan-Finney model. The main processes in this model are based on the Morgan-Morgan-Finney soil erosion model, and it is suitable for estimating surface runoff and sediment redistribution patterns in seasonal climate regions with complex surface configurations. We achieved temporal flexibility by utilizing daily time steps, which is suitable for regions with concentrated seasonal rainfall. We introduce the proportion of impervious surface cover as a parameter to reflect its impacts on soil erosion through blocking water infiltration and protecting the soil from detachment. Also, several equations and sequences of sub-processes are modified from the previous model to better represent physical processes. From the sensitivity analysis using the Sobol' method, the DMMF model shows the rational response to the input parameters which is consistent with the result from the previous versions. To evaluate the model performance, we applied the model to two potato fields in South Korea that had complex surface configurations using plastic covered ridges at various temporal periods during the monsoon season. Our new model shows acceptable performance for runoff and the sediment loss estimation (NSE ≥ 0.63, |PBIAS| ≤ 17.00, and RSR ≤ 0.57). Our findings demonstrate that the DMMF model is able to predict the surface runoff and sediment redistribution patterns for cropland with complex surface configurations.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.