Nitrate Pathways, Processes, and Timing in an Agricultural Karst System: Development and Application of a Numerical Model

An edited version of this paper was published by AGU. Copyright 2019 American Geophysical Union.Nitrogen (N) contamination within agricultural‐karst landscapes and aquifers is widely reported; however, the complex hydrological pathways of karst make N fate difficult to ascertain. We developed a hydrologic and N numerical model for agricultural‐karst, including simulation of soil, epikarst, phreatic, and quick flow pathways as well as biochemical processes such as nitrification, mineralization, and denitrification. We tested the model on four years of nitrate (NO3−) data collected from a phreatic conduit and an overlying surface channel in the Cane Run watershed, Kentucky, USA. Model results indicate that slow to moderate flow pathways (phreatic and epikarst) dominate the N load and account for nearly 90% of downstream NO3− delivery. Further, quick flow pathways dilute NO3− concentrations relative to background aquifer levels. Net denitrification distributed across soil, epikarst, and phreatic water removes approximately 36% of the N inputs to the system at rates comparable to nonkarst systems. Evidence is provided by numerical modeling that NO3− accumulation via evapotranspiration in the soil followed by leaching through the epikarst acts as a control on spring NO3− concentration and loading. Compared to a fluvial‐dominated immature karst system, mature‐karst systems behave as natural detention basins for NO3−, temporarily delaying NO3− delivery to downstream waters and maintaining elevated NO3− concentrations for days to weeks after hydrologic activity ends. This study shows the efficacy of numerical modeling to elucidate complex pathways, processes, and timing of N in karst systems

Modelling the impacts of agricultural management practices on river water quality in Eastern England

Agricultural diffuse water pollution remains a notable global pressure on water quality, posing risks to aquatic ecosystems, human health and water resources and as a result legislation has been introduced in many parts of the world to protect water bodies. Due to their efficiency and cost-effectiveness, water quality models have been increasingly applied to catchments as Decision Support Tools (DSTs) to identify mitigation options that can be introduced to reduce agricultural diffuse water pollution and improve water quality. In this study, the Soil and Water Assessment Tool (SWAT) was applied to the River Wensum catchment in eastern England with the aim of quantifying the long-term impacts of potential changes to agricultural management practices on river water quality. Calibration and validation were successfully performed at a daily time-step against observations of discharge, nitrate and total phosphorus obtained from high-frequency water quality monitoring within the Blackwater sub-catchment, covering an area of 19.6 km2. A variety of mitigation options were identified and modelled, both singly and in combination, and their long-term effects on nitrate and total phosphorus losses were quantified together with the 95% uncertainty range of model predictions. Results showed that introducing a red clover cover crop to the crop rotation scheme applied within the catchment reduced nitrate losses by 19.6%. Buffer strips of 2 m and 6 m width represented the most effective options to reduce total phosphorus losses, achieving reductions of 12.2% and 16.9%, respectively. This is one of the first studies to quantify the impacts of agricultural mitigation options on long-term water quality for nitrate and total phosphorus at a daily resolution, in addition to providing an estimate of the uncertainties of those impacts. The results highlighted the need to consider multiple pollutants, the degree of uncertainty associated with model predictions and the risk of unintended pollutant impacts when evaluating the effectiveness of mitigation options, and showed that high-frequency water quality datasets can be applied to robustly calibrate water quality models, creating DSTs that are more effective and reliable

NeuralHydrology -- Interpreting LSTMs in Hydrology

Despite the huge success of Long Short-Term Memory networks, their applications in environmental sciences are scarce. We argue that one reason is the difficulty to interpret the internals of trained networks. In this study, we look at the application of LSTMs for rainfall-runoff forecasting, one of the central tasks in the field of hydrology, in which the river discharge has to be predicted from meteorological observations. LSTMs are particularly well-suited for this problem since memory cells can represent dynamic reservoirs and storages, which are essential components in state-space modelling approaches of the hydrological system. On basis of two different catchments, one with snow influence and one without, we demonstrate how the trained model can be analyzed and interpreted. In the process, we show that the network internally learns to represent patterns that are consistent with our qualitative understanding of the hydrological system.Comment: Pre-print of published book chapter. See journal reference and DOI for more inf

Comparative analysis of NOAA REFM and SNB 3 GEO tools for the forecast of the fluxes of high-energy electrons at GEO

Reliable forecasts of relativistic electrons at geostationary orbit (GEO) are important for the mitigation of their hazardous effects on spacecraft at GEO. For a number of years the Space Weather Prediction Center at NOAA has provided advanced online forecasts of the fluence of electrons with energy >2 MeV at GEO using the Relativistic Electron Forecast Model (REFM). The REFM forecasts are based on real-time solar wind speed observations at L1. The high reliability of this forecasting tool serves as a benchmark for the assessment of other forecasting tools. Since 2012 the Sheffield SNB3GEO model has been operating online, providing a 24 h ahead forecast of the same fluxes. In addition to solar wind speed, the SNB3GEO forecasts use solar wind density and interplanetary magnetic field Bz observations at L1.The period of joint operation of both of these forecasts has been used to compare their accuracy. Daily averaged measurements of electron fluxes by GOES 13 have been used to estimate the prediction efficiency of both forecasting tools. To assess the reliability of both models to forecast infrequent events of very high fluxes, the Heidke skill score was employed. The results obtained indicate that SNB3GEO provides a more accurate 1 day ahead forecast when compared to REFM. It is shown that the correction methodology utilized by REFM potentially can improve the SNB3GEO forecast

Identifying streamgage networks for maximizing the effectiveness of regional water balance modeling

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/98795/1/wrcr20233.pd

Deriving Hourly Evapotranspiration Rates with SEBS: A Lysimetric Evaluation

Numerous energy balance (EB) algorithms have been developed to use remote sensing data for mapping evapotranspiration (ET) on a regional basis. Adopting any single or combination of these models for an operational ET remote sensing program requires a thorough evaluation. The Surface Energy Balance System (SEBS) was evaluated for its ability to estimate hourly ET rates of summer tall and short crops grown in the Texas High Plains by using 15 Landsat 5 Thematic Mapper scenes acquired during 2006 to 2009. Performance of SEBS was evaluated by comparing estimated hourly ET values with measured ET data from four large weighing lysimeters, each located at the center of a 4.3 ha field in the USDA-ARS Conservation and Production Research Laboratory in Bushland, TX. The performance of SEBS in estimating hourly ET was good for crops under both irrigated and dryland conditions. A locally derived, surface albedo-based soil heat flux (G) model further improved the G estimates. Root mean square error and mean bias error were 0.11 and −0.005 mm h−1, respectively, and the Nash–Sutcliff model efficiency was 0.85 between the measured and calculated hourly ET. Considering the equal or better performance with a minimal amount of ancillary data as compared to with other EB algorithms, SEBS is a promising tool for use in an operational ET remote sensing program in the semiarid Texas High Plains. However, thorough sensitivity and error propagation analyses of input variables to quantify their impact on ET estimations for the major crops in the Texas High Plains under different agroclimatological conditions are needed before adopting the SEBS into operational ET remote sensing programs for irrigation scheduling or other purposes

The INtegrated CAtchment model of phosphorus dynamics (INCA-P): description and demonstration of new model structure and equations

INCA-P is a dynamic, catchment-scale phosphorus model which has been widely applied during the last decade. Since its original release in 2002, the model structure and equations have been significantly altered during several development phases. Here, we provide the first full model description since 2002 and then test the latest version of the model (v1.4.4) in a small rural catchment in northeast Scotland. The particulate phosphorus simulation was much improved compared to previous model versions, whilst the latest sorption equations allowed us to explore the potential time lags between reductions in terrestrial inputs and improvements in surface water quality, an issue of key policy relevance. The model is particularly suitable for use as a research tool, but should only be used to inform policy and land management in data-rich areas, where parameters and processes can be well-constrained. More long-term data is needed to parameterise dynamic models and test their predictions

How land use/land cover changes can affect water, flooding and sedimentation in a tropical watershed: a case study using distributed modeling in the Upper Citarum watershed, Indonesia

[EN] Human activity has produced severe LULC changes within the Upper Citarum watershed and these changes are predicted to continue in the future. With an increase in population parallel to a 141% increment in urban areas, a reduction of rice fields and the replacement of forests with cultivations have been found in the past. Accordingly, LCM model was used to forecast the LULC in 2029. A distributed model called TETIS was implemented in the Upper Citarum watershed to assess the impact of the different historical and future LULC scenarios on its water and sediment cycles. This model was calibrated and validated with different LULCs. For the implementation of the sediment sub-model, it was crucial to use the bathymetric information of the reservoir located at the catchment's outlet. Deforestation and urbanization have been shown to be the most influential factors affecting the alteration of the hydrological and sedimentological processes in the Upper Citarum watershed. The change of LULC decreases evapotranspiration and as a direct consequence, the water yield increased by 15% and 40% during the periods 1994-2014 and 2014-2029, respectively. These increments are caused by the rise of three components in the runoff: overland flow, interflow and base flow. Apart from that, these changes in LULC increased the area of non-tolerable erosion from 412 km(2) in 1994 to 499 km(2) in 2029. The mean sediment yield increased from 3.1 Mton -yr(-1) in the 1994 LULC scenario to 6.7 Mton-yr(-1) in the 2029 LULC scenario. An increment of this magnitude will be catastrophic for the operation of the Saguling Dam.This study was partially funded by the Spanish Ministry of Economy and Competitiveness through the research projects TETISMED (CGL2014-58,127-C3-3-R) and TETISCHANGE (RTI2018-093717-B-I00). The authors are also thankful to the Directorate General of Higher Education of Indonesia (DIKTI) for the Ph.D. funding of the first author.Siswanto, SY.; Francés, F. (2019). How land use/land cover changes can affect water, flooding and sedimentation in a tropical watershed: a case study using distributed modeling in the Upper Citarum watershed, Indonesia. Environmental Earth Sciences. 78(17):1-15. https://doi.org/10.1007/s12665-019-8561-0S115781