Evaluating hydrologic responses to soil characteristics using SWAT model in a paired-watersheds in the Upper Blue Nile Basin

Watershed responses are affected by the watershed characteristics and rainfall events. The characteristics of soil layers are among the fundamental characteristics of a watershed and they are input to hydrologic modeling similar to topography and land use/cover. Although the roles of soils have been perceived, there are limited studies that quantify the role of soil characteristics on watershed runoff responses due to the lack of field datasets. Using two adjacent watersheds (Ribb and Gumara) which have a significant different runoff response with a similar characterstics except geological settings (including soil characteristics), we studied the effects of soil characteristics on runoff and water balance. The Soil and Water Assessment Tool (SWAT) was used to simulate the surface runoff response at the outlet of the watershed and the optimal model parameters distribution was tested with a non-parametric test for similarity. Results indicated that SWAT model captured the observed flow very well with a Nash-Sutcliffe Efficiency (NSE) of greater than 0.74 and with a PBIAS of less than 10% for both calibration and validation period. The comparison of the optimal model parameter distributions of the SWAT model showed that the watershed characteristics could be uniquely defined and represented by a hydrologic model due to the differences in the soils. Using field observations and modeling experiments, this study demonstrates how sensitive watershed hydrology is to soils, emphasizing the importance of accurate soil information in hydrological modeling. We conclude that due emphasis should be given to soil information in hydrologic analysis

Remote Sensing and Ground-Based Weather Forcing Data Analysis for Streamflow Simulation

Hydrological simulation, based on weather inputs and the physical characterization of the watershed, is a suitable approach to predict the corresponding streamflow. This work, carried out on four different watersheds, analyzed the impacts of using three different meteorological data inputs in the same model to compare the model’s accuracy when simulated and observed streamflow are compared. Meteorological data from the Daily Global Historical Climatology Network (GHCN-D), National Land Data Assimilation Systems (NLDAS) and the National Operation Hydrological Remote Sensing Center’s Interactive Snow Information (NOHRSC-ISI) were used as an input into the Soil and Water Assessment Tool (SWAT) hydrological model and compared as three different scenarios on each watershed. The results showed that meteorological data from an assimilation system like NLDAS achieved better results than simulations performed with ground-based meteorological data, such as GHCN-D. However, further work needs to be done to improve both the datasets and model capabilities, in order to better predict streamflow

Assessment of Optional Sediment Transport Functions via the Complex Watershed Simulation Model SWAT

The Soil and Water Assessment Tool 2012 (SWAT2012) offers four sediment routing methods as optional alternatives to the default simplified Bagnold method. Previous studies compared only one of these alternative sediment routing methods with the default method. The proposed study evaluated the impacts of all four alternative sediment transport methods on sediment predictions: the modified Bagnold equation, the Kodoatie equation, the Molinas and Wu equation, and the Yang equation. The Arroyo Colorado Watershed, Texas, USA, was first calibrated for daily flow. The sediment parameters were then calibrated to monthly sediment loads, using each of the four sediment routing equations. An automatic calibration tool—Integrated Parameter Estimation and Uncertainty Analysis Tool (IPEAT)—was used to fit model parameters. The four sediment routing equations yielded substantially different sediment sources and sinks. The Yang equation performed best, followed by Kodoatie, Bagnold, and Molinas and Wu equations, according to greater model goodness-of-fit (represented by higher Nash–Sutcliffe Efficiency coefficient and percent bias closer to 0) as well as lower model uncertainty (represented by inclusion of observed data within 95% confidence interval). Since the default method (Bagnold) does not guarantee the best results, modelers should carefully evaluate the selection of alternative methods before conducting relevant studies or engineering projects

Improving In-Stream Nutrient Routines in Water Quality Models Using Stable Isotope Tracers: A Review and Synthesis

Water quality models serve as an economically feasible alternative to quantify fluxes of nutrient pollution and to simulate effective mitigation strategies; however, their applicability is often questioned due to broad uncertainties in model structure and parameterization, leading to uncertain outputs. We argue that reduction of uncertainty is partially achieved by integrating stable isotope data streams within the water quality model architecture. This article outlines the use of stable isotopes as a response variable within water quality models to improve the model boundary conditions associated with nutrient source provenance, constrain model parameterization, and elucidate shortcomings in the model structure. To assist researchers in future modeling efforts, we provide an overview of stable isotope theory; review isotopic signatures and applications for relevant carbon, nitrogen, and phosphorus pools; identify biotic and abiotic processes that impact isotope transfer between pools; review existing models that have incorporated stable isotope signatures; and highlight recommendations based on synthesis of existing knowledge. Broadly, we find existing applications that use isotopes have high efficacy for reducing water quality model uncertainty. We make recommendations toward the future use of sediment stable isotope signatures, given their integrative capacity and practical analytical process. We also detail a method to incorporate stable isotopes into multi-objective modeling frameworks. Finally, we encourage watershed modelers to work closely with isotope geochemists to ensure proper integration of stable isotopes into in-stream nutrient fate and transport routines in water quality models

Optimization of the hydrodynamic characteristics of a karst conduit with CFPv2 coupled to OSTRICH

The final publication is available at Elsevier via https://dx.doi.org/10.1016/j.jhydrol.2018.10.050 © 2018. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/In order to better define the characteristics of a karst conduit, an integrated hydrogeological study including numerical modeling using CFPv2 is conducted at a karst aquifer in the Zagros Mountain Region of Iran. The Sarvak limestone aquifer in the Nil Anticline is the main karst aquifer of the study area with major groundwater discharge taking place at Sarkur spring. An annual water balance and a dye tracing test confirmed that the karst system is mainly recharged through rainfall and the Maroon River. Several depressions are observed along the banks of the river with a major one classified as a sinkhole used for dye injection. A groundwater flow model was developed based on the available hydrogeological information. A probable direct conduit flow path with an estimated groundwater flow velocity of 96 m/h is estimated between the injection point and the Sarkur spring. Four scenarios are assumed to simulate the probable conduit flow path using the CFPv2 code. As one of the first attempts in regional groundwater flow modeling of a karst aquifer, CFPv2 is automatically calibrated with field measurements of spring discharge and a dye breakthrough curve through a parameter estimation code OSTRICH to optimize the characteristics of the conduit through the minimization of the weighted sum of square error. Simulated results reveal that a conduit with a diameter of 2.9 m is required to adequately simulate spring discharge and dye tracer migration between the injection and discharge points. Our new approach (linking of CFPv2 and OSTRICH) provides a deeper understanding of groundwater flow and solute transport in karst terrains even when available data are limited and the approach should be applicable to other areas.Shiraz UniversityUniversity of Waterlo

Runoff simulation of ungauged catchments : importance in the Nepalese context

Nepal is a landlocked country in the foothills of the Himalayan region in South Asia and a country endowed with rich water resources. However, the country is unable to utilize and manage the full potential of available water resources. One of the reasons for this is the lack of an adequate network of river gauging stations necessary to collect hydrologic data. Installation of hydrological stations is an expensive proposition and not financially viable for small water resources projects (water supply, irrigation, mini and micro-hydro projects). This research aims to address the challenges via an alternative strategy - i.e. the use of a hydrological model which can reliably simulate runoff in ungauged catchments even in the absence of adequate hydrologic data. SWAT (Soil & Water Assessment Tool), a popular simulation model with ArcGIS and QGIS interface, was chosen to simulate flow in an ungauged catchment in the mid-western region of Nepal. The model was applied to the West Rapti River basin using five years (1981-1985) of data from the Global Runoff Data Centre (GRDC). The GRDC was the only source, and the dataset was incomplete, limiting the model calibration and validation process. This limitation was addressed by using another simulation model, HEC-HMS (Hydrologic Engineering Centre’s Hydrologic Modeling System), for comparison. The results of the SWAT model were compared with those from HEC-HMS, one of the most widely used rainfall-runoff simulation models. Comparative analysis showed that both models generated comparable results. Historical rainfall data (1979-2009) were extracted from the Global Weather Data for SWAT to predict the rainfall trend in the West Rapti Watershed. This trend in rainfall pattern was used to extract rainfall and simulate runoff for 2023 to 2026, considering rainfall data of 2013 as a baseline. The simulated results showed a minor shift in time to peak and increased peak discharge. Similarly, the simulated runoff trends matched perfectly with the observed rainfall trend in SWAT. Thus, the results proved the reliability of SWAT to simulate runoff in the West Rapti Basin. The conclusion was drawn that the SWAT model can be used reliably to predict runoff in ungauged catchments that assist with managing water resources and contribute to the development of Nepal’s economy

Modelling the impacts of land-used and climate change in Skudai river watershed

Predicting the impact of land-use, climate change and Best Management Practices (BMPs) on a watershed is imperative for effective management of aquatic ecosystems, floods, pollutant control and maintenance of water quality standard in a tropical climate. Based on the prediction, unique information can be derived that is critical to the watershed management under dynamic environmental conditions. The study seeks to evaluate how land-use and climate change influences the hydrology, sediments, and water quality of an urbanized tropical watershed in which the land-use is controlled by urban development as observed from historical and projected land covers. Therefore, the response of a tropica l watershed and its river system under climate and land-use changes were evaluated using Skudai River watershed as a case study. Seven land-use scenarios from the year 1989 to 2039 were developed using remote sensing teclmiques, and nine projected climate change scenarios were derived using dynamically downscaled model from the based projection under representative concentration pathways (RCPs) scenarios. These scenarios were integrated into the Hydrological Simulation Program FORTRAN (HSPF) model to determine the impact of land-use , climate change, and pollutants control via best management practices in a tropical watershed system. The model was calibrated and validated from 2002 to 2014, and the performance coefficients showed a good correlation between simulated and observed streamflow, water temperature, dissolved oxygen (DO), biochemical oxygen demand (BOD), ammonia nitrogen (NH3-N), nitrate nitrogen (N03-N), and orthophosphate (P04) concentrations. The output of the validated model under land-use changes showed that the hydrological water balance of the watershed changes with total runoff as the primary source of water loss. For streamflows and in-stream concentrations (NH3-N, N03-N, and P04) , as the streamflow increases, NH3-N and P04 concentrations increase while N03-N concentration showed low response as compared to the other two concentrations. As urban development increased from 18.2% to 49.2%, nutrient influx such as total nitrogen (TN) and total phosphorus (TP) loads increased from 3080 to 4560 kg/yr and from 130 to 270 kg/yr, respectively. Furthermore, TN to TP ratio changed from 8.3:1 to 7:1, an indication that the rivers are receiving excess nutrients flows which might result in eutrophication at the downstream of the watershed . The amount of sediment load produced in the watershed decreased by approximately 17.8% as a result of the changes in land-use derived from urban development. Further analysis ofthe results showed that climate change with high rainfall and increase in air temperature do not affect DO concentration and water temperature in comparison to climate change with low rainfall. Implementation of multiple detention pond BMPs in identified Critical Source Areas (CSAs) reduced pollutant loads by 14% to 27% as compared to watershed without any BMPS, independent ofclimate and landuse changes. Analysis ofBMPs using existing and future land-use is very important to ensure their effectiveness to control and maintain water quality. This study provides a basis to develop water resource management in an urban watershed and be resilient to land-use and climate changes

Long-term-robust adaptation strategies for reservoir operation considering magnitude and timing of climate change: application to Diyala River Basin in Iraq

2020 Spring.Includes bibliographical references.Vulnerability assessment due to climate change impacts is of paramount importance for reservoir operation to achieve the goals of water resources management. This requires accurate forcing and basin data to build a valid hydrology model and assessment of the sensitivity of model results to the forcing data and uncertainty of model parameters. The first objective of this study is to construct the model and identify its sensitivity to the model parameters and uncertainty of the forcing data. The second objective is to develop a Parametric Regional Weather Generator (RP-WG) for use in areas with limited data availability that mimics observed characteristics. The third objective is to propose and assess a decision-making framework to evaluate pre-specified reservoir operation plans, determine the theoretical optimal plan, and identify the anticipated best timeframe for implementation by considering all possible climate scenarios. To construct the model, the Variable Infiltration Capacity (VIC) platform was selected to simulate the characteristics of the Diyala River Basin (DRB) in Iraq. Several methods were used to obtain the forcing data and they were validated using the Kling–Gupta efficiency (KGE) metric. Variables considered include precipitation, temperature, and wind speed. Model sensitivity and uncertainty were examined by the Generalized Likelihood Uncertainty Estimation (GLUE) and the Differential Evolution Adaptive Metropolis (DREAM) techniques. The proposed RP-WG was based on (1) a First-order, Two-state Markov Chain to simulate precipitation occurrences; (2) use of Wilks' technique to produce correlated weather variables at multiple sites with conservation of spatial, temporal, and cross correlations; and (3) the capability to produce a wide range of synthetic climate scenarios. A probabilistic decision-making framework under nonstationary hydroclimatic conditions was proposed with four stages: (1) climate exposure generation (2) supply scenario calculations, (3) demand scenario calculations, and (4) multi-objective performance assessment. The framework incorporated a new metric called Maximum Allowable Time to examine the timeframe for robust adaptations. Three synthetic pre-suggested plans were examined to avoid undesirable long-term climate change impacts, while the theoretical-optimal plan was identified by the Non-dominated Sorting Genetic Algorithm II. The multiplicative random cascade and Schaake Shuffle techniques were used to determine daily precipitation data, while a set of correction equations was developed to adjust the daily temperature and wind speed. The depth of the second soil layer caused most sensitivity in the VIC model, and the uncertainty intervals demonstrated the validity of the VIC model to generate reasonable forecasts. The daily VIC outputs were calibrated with a KGE average of 0.743, and they were free from non-normality, heteroscedasticity, and auto-correlation. Results of the PR-WG evaluation show that it exhibited high values of the KGE, preserved the statistical properties of the observed variables, and conserved the spatial, temporal, and cross correlations among the weather variables at all sites. Finally, risk assessment results show that current operational rules are robust for flood protection but vulnerable in drought periods. This implies that the project managers should pay special attention to the drought and spur new technologies to counteract. Precipitation changes were dominant in flood and drought management, and temperature and wind speed changes effects were significant during drought. The results demonstrated the framework's effectiveness to quantify detrimental climate change effects in magnitude and timing with the ability to provide a long-term guide (and timeframe) to avert the negative impacts

Variance Decomposition of Forecasted Water Budget and Sediment Processes under Changing Climate in Fluvial and Fluviokarst Systems

Variance decomposition is the partitioning of different factors affecting the variance structure of a response variable. The present research focuses on future streamflow and sediment transport processes projections as the response variables. The authors propose using numerous climate factors and hydrological modeling factors that can cause any response variable to vary from historic to future conditions in any given watershed system. The climate modeling factors include global climate model, downscaling method, emission scenario, project phase, bias correction. The hydrological modeling factor includes hydrological model parametrization, and meteorological variable inclusion in the analysis. This research uses a wide spectrum of data, including climate data of precipitation and temperature from GCM results, and observations of meteorological data, streamflow and spring flow data, and sediment yield data. This research focuses on employing an off-the-shelf hydrological model and developing different numerical models (using MATLAB) for simulating sediment transport processes and water movement in an epigenetic karst system. With regards to variance decomposition, the approach is to use a mixed statistical method of linear and nonlinear analysis by means of analysis of variance (ANOVA) and artificial neural networks (ANN) respectively. All the computational tools that will be used to perform the statistics are provided by SPSS software. Two study sites are considered in this work including South Elkhorn watershed and Cave Run watershed. South Elkhorn watershed is a fluvial system and is located in Lexington, Kentucky, USA. This system is characterized as a wet, temperate region in the central and eastern United States where a change in the climate is projected. The mean streamflow, extreme streamflow, and sediment processes forecast are investigated in this watershed. Royal Spring watershed is a fluviokarst system and is adjacent to the South Elkhorn watershed. In this watershed we investigate the water pathway connectivity as well as the impact of climate change on the mean annual spring flow and streamflow. Analysis of variance results indicate that the difference in forecast and hindcast mean streamflow predictions is a function of GCM type, climate model project phase, and downscaling approach. Predicted average monthly change in streamflow tends to follow precipitation changes and result in a net increase in the average annual precipitation and streamflow by 10% and 11%, respectively, when comparing historical period (1980-2000) to the future period (2045-2065). Results show that the relative change of streamflow maxima was not dependent on systematic variance from the annual maxima method versus peak over threshold method. However, it was dependent all climate modeling factors. Ensemble projections forecast an increase of streamflow maxima of 51% for 100-year streamflow event. Hydrologic model parameterization was the greatest source of variance impacting forecasted sediment transport variables. Hydrologic inputs from climate change including forecasted precipitation, temperature, relative humidity, solar radiation and wind speed all impacted sediment transport. Ensemble average forecasts sediment yield to increase by 14% for the Upper South Elkhorn watershed. The numerical model of the Cave Run/ Royal Spring watershed suggests 30 to 45% of surface stream discharge originates from in-stream swallet reversal and hillside springs. Also, the hydrology of the floviokarst system might be altered by the impact of climate change where an increase in the surface flow and spring flow is projected to be 8.8% and 12.2%, respectively. The results show that the change in pathway connectivity is important on seasonal bases and follows the seasonal change in precipitations