Application of Automated Geospatial Watershed Assessment (AGWA) Tool to Evaluate the Sediment Yield in a Semi-arid Region: Case Study, Kufranja Basin-Jordan

Prediction of sediment yield from catchments is essential in the investigation of reservoir sedimentation and other hydrological and geological studies. Many methods have been used in the prediction of sediment yield. Soil and Water Assessment Tool (SWAT) is a newly developed model that can be applied to rural watershed. SWAT model has used Modified Universal Soil Loss Equation (MUSLE) in sediment calculation. The Automated Geospatial Watershed Assessment Tool (AGWA) is a GIS based watershed modeling tool. This paper improved a hydrological modeling using modeling environment AGWA and SWAT model to evaluate the sediment yield in Kufranja basin in Jordan. The sediment yield has been calculated at three proposed dam sites in the basin. The calibration process depended on the most sensitive parameters in SWAT model. Long term rainfall series were used in the modeling process. AGWA studies the change in the most sensitive parameter in the SWAT model. The change in this parameter can be considered as different scenarios in Kufranja basin

Seafloor characterization using airborne hyperspectral co-registration procedures independent from attitude and positioning sensors

The advance of remote-sensing technology and data-storage capabilities has progressed in the last decade to commercial multi-sensor data collection. There is a constant need to characterize, quantify and monitor the coastal areas for habitat research and coastal management. In this paper, we present work on seafloor characterization that uses hyperspectral imagery (HSI). The HSI data allows the operator to extend seafloor characterization from multibeam backscatter towards land and thus creates a seamless ocean-to-land characterization of the littoral zone

Radar Z-R relationship for summer monsoon storms in Arizona

Radar-based estimates of rainfall rates and accumulations are one of the principal tools used by the National Weather Service (NWS) to identify areas of extreme precipitation that could lead to flooding. Radar-based rainfall estimates have been compared to gauge observations for 13 convective storm events over a densely instrumented, experimental watershed to derive an accurate reflectivity-rainfall rate (i.e., Z-R) relationship for these events. The resultant Z-R relationship, which is much different than the NWS operational Z-R, has been examined for a separate, independent event that occurred over a different location. For all events studied, the NWS operational Z-R significantly overestimates rainfall compared to gauge measurements. The gauge data from the experimental network, the NWS operational rain estimates, and the improved estimates resulting from this study have been input into a hydrologic model to "predict" watershed runoff for an intense event. Rainfall data from the gauges and from the derived Z-R relation produce predictions in relatively good agreement with observed streamflows. The NWS Z-R estimates lead to predicted peak discharge rates that are more than twice as large as the observed discharges. These results were consistent over a relatively wide range of subwatershed areas (4-148 km2). The experimentally derived Z-R relationship may provide more accurate radar estimates for convective storms over the southwest United States than does the operational convective Z-R used by the NWS. These initial results suggest that the generic NWS Z-R relation, used nationally for convective storms, might be substantially improved for regional application. © 2005 American Meteorological Society

A lake-centric geospatial database to guide research and inform management decisions in an Arctic watershed in northern Alaska experiencing climate and land-use changes

Lakes are dominant and diverse landscape features in the Arctic, but conventional land cover classification schemes typically map them as a single uniform class. Here, we present a detailed lake-centric geospatial database for an Arctic watershed in northern Alaska. We developed a GIS dataset consisting of 4362 lakes that provides information on lake morphometry, hydrologic connectivity, surface area dynamics, surrounding terrestrial ecotypes, and other important conditions describing Arctic lakes. Analyzing the geospatial database relative to fish and bird survey data shows relations to lake depth and hydrologic connectivity, which are being used to guide research and aid in the management of aquatic resources in the National Petroleum Reserve in Alaska. Further development of similar geospatial databases is needed to better understand and plan for the impacts of ongoing climate and land-use changes occurring across lake-rich landscapes in the Arctic

Evaluating ephemeral gullies with a process-based topographic index model

Soil conservation practices have been implemented to control soil degradation from sheet and rill erosion, but excessive sediment runoff remains among the most prevalent water quality problems in the world. Ephemeral gully (EG) erosion has been recognized as a major source of sediment in agricultural watersheds; thus, predicting location and length of EGs is important to assess sediment contribution from EG erosion. Geomorphological models are based on topographic information and ignore other important factors such as precipitation, soil, topography, and land use/land management practices, whereas physically based models are complex, require detailed input information, and are difficult to apply to larger areas. In this study, an approach was developed to incorporate a process-based Overland Flow-Turbulent (OFT) EG model that contained factors accounting for drainage area, surface roughness, slope, soil critical shear stress, and surface runoff in the ArcGIS environment. Two hydrologic models, Soil Water Assessment Tool (SWAT) and ArcCN-Runoff (ACR), were adopted to simulate precipitation excess in Goose Creek watershed in central Kansas, USA. These two realizations of the OFT model were compared with the Slope-Area (SA) topographic index model for accuracy of EG location identification and length calculation. The critical threshold index in the SA model was calibrated in a single field in the watershed prior to EG identification whereas the OFT models were uncalibrated. Results demonstrated overall similar performance between calibrated SA model and uncalibrated OFT-SWAT model, and both outperformed the uncalibrated OFT-ACR model. In simulation of EG location, the OFT-SWAT model resulted in 12% fewer false negatives but 8% more false positives than the SA model, compared with 19% fewer false positive and 6% more false negatives than the OFT-ACR model. Greater errors in runoff estimation by ACR translated directly into errors in EG simulation. All models over-predicted EG lengths compared with observed data, though OFT-SWAT and SA models did so with better fit exceedance probability curves, about zero Nash-Sutcliff model efficiency and ≤40% bias compared to -3 model efficiency and >100% bias for OFT-ACR. Success of the uncalibrated OFT-SWAT model in producing satisfactory predictions of EG location and EG length shows promise for process-based EG simulation. The OFT-SWAT model used data and parameters also commonly used for SWAT model development, which should simplify its adoption to other watersheds and regions. Further testing is needed to determine the robustness of the OFT-SWAT model to dissimilar field and hydrologic conditions. It is expected that inclusion of more site-specific physical properties in OFT-SWAT would improve model performance in predicting location and length of EGs, which is essential for accurate estimation of EG sediment erosion rates

Estimation Of Runoff And Erosion Rates Using Agwa - Kineros2 Model: Application To A Mediterranean Watershed

The Mediterranean area is classified as a region highly threatened by water erosion, which depends largely on climatic aggressiveness, erodible soils, sparse vegetation, and irrational human activity. Tleta watershed belongs to a young mountain ridge (Rif), readily erodible and highly vulnerable to water erosion. To assess the extent of this phenomenon, AGWA tool coupled with KINEROS2 (K2) model was used to predict the specific degradation and the hydrological functioning of the studied watershed. The data required consisted of topography, land use, soil type, and precipitation. The model simulations will make it possible to estimate the sediment load deposited at the Ibn Batouta dam, which results from upstream erosion. The evaluation criteria for the predictive skill of K2 model when comparing observed and simulated data are the coefficient of determination (R2) and the Nash–Sutcliffe model efficiency coefficient (NSE). These two coefficients are respectively (R² = 0.99, NSE = 0.71) and (R² = 0.99, NSE = 0.72) for runoff and sediments yield for calibration. For the validation process, these two coefficients are (R² = 0.99 and NSE = 0.98) for runoff and (R² = 0.99 and NSE = 0.97) for sediments yield. This allows us to conclude that the predictive accuracy of the model is promising

Training of Crisis Mappers and Map Production from Multi-sensor Data: Vernazza Case Study (Cinque Terre National Park, Italy)

This aim of paper is to presents the development of a multidisciplinary project carried out by the cooperation between Politecnico di Torino and ITHACA (Information Technology for Humanitarian Assistance, Cooperation and Action). The goal of the project was the training in geospatial data acquiring and processing for students attending Architecture and Engineering Courses, in order to start up a team of "volunteer mappers". Indeed, the project is aimed to document the environmental and built heritage subject to disaster; the purpose is to improve the capabilities of the actors involved in the activities connected in geospatial data collection, integration and sharing. The proposed area for testing the training activities is the Cinque Terre National Park, registered in the World Heritage List since 1997. The area was affected by flood on the 25th of October 2011. According to other international experiences, the group is expected to be active after emergencies in order to upgrade maps, using data acquired by typical geomatic methods and techniques such as terrestrial and aerial Lidar, close-range and aerial photogrammetry, topographic and GNSS instruments etc.; or by non conventional systems and instruments such us UAV, mobile mapping etc. The ultimate goal is to implement a WebGIS platform to share all the data collected with local authorities and the Civil Protectio

Sediment Yield Problems in Khassa Chai Watershed Using Hydrologic Models

Upland erosion and sedimentation are one of the severe problems which faces dams as sediments occupy spaces within reservoirs storage, hence, decreasing live water storage which is the main purpose of dam’s construction. Iraq is one of the countries that will face a significant shortage of water income as a result of both the increment in water demand and of the reduction of water shares from the source countries. Thus, the existing dams in Iraq represent a strategic resource to fulfill water demands, and the sedimentation at these dams is studied to assess the quantity of sediments that reach to these reservoirs and decrease available water volume and useful life of reservoir. In the current study, Khassa Chai Dam is located in the Northeast of Iraq and its main watershed basin covers an area of about 412 km2 between Kirkuk and Al Sulaymaniyah Governorates has been selected to estimate and predict the amount of sediment yield based on 30 years of daily climate data and the events of different intensity rainstorms. Automated geospatial watershed assessment (AGWA) tool model has been used to simulate Khassa Chai Dam catchment area. This model utilizes the geographic information system (GIS) application to analyze the required data from GIS layer for digital elevation model, soil type, land use, and land cover by interference with the required climate data. The key components of AGWA model are the soil and water assessment tool model and kinematic runoff and erosion (KINEROS) model which are able to simulate complex watershed behavior to explicitly account for spatial variability of soils, rainfall distribution patterns, and vegetation. The hydrologic characteristics for Khassa Chai catchment area according to the SWAT outputs show that the most erosive sub-basins are not able to deliver the eroded material or sediments to the reservoir due to their transmission losses, percolation, and other minor obstacles. KINEROS model simulation for sediment yield is much closer to the behavior of Khassa Chai watershed in erosion and sediment transport according to the single storm events and for individually selected sub-watersheds which are closed in their location to reservoir inlet

A Study of Geographic Information System-Based Watershed Processing for Hydrologic Analysis of Ungauged Watersheds

The increasing application of geographic information system (GIS) technology in watershed modeling makes is necessary to further evaluate its impacts on runoff characteristics as a basis for improved hydrologic analysis in ungauged watersheds. Experts in the field of water resources and hydrology have recommended the practice of subdivision when modeling a watershed, and the use of observed data from hydrologically similar watershed to calibrate and validate an ungauged watershed’s model. However, previous studies have failed to adequately address the issues of watershed heterogeneity, spatial and temporal variability in physical parameters, GIS data resolution issues, including artifacts in automated extraction of topographic attributes from elevation datasets. This study utilized the US Army Corps of Engineers Hydrologic Engineering Center Hydrologic Modeling System (HEC-HMS) to evaluate the effects of watershed subdivision and input data resolution on peak discharge in ungauged watersheds. To better understand the underlying processes in ungauged watershed hydrology, runoff hydrographs were simulated at the outlets of study areas located in different hydrological subregions and subdivided into different subdivision scenarios or levels. Simulation results show that total channel slopes and total flow lengths increased with further subdivision, resulting in high peak discharges. Similarly, runoff hydrographs at the outlets of different resolution models were simulated and analyzed. Simulation results indicate that peak discharge values increased as finer resolution datasets were resampled to coarser resolutions with a slight reduction in the sizes of drainage areas. A better understanding of a watershed’s runoff characteristics is a basis for improved hydrologic analysis of ungauged watersheds