This study describes the application of a water run-off model for Lake Santa Ana, Mexico, developed through the combined application of two simulation models: the Watershed Modelling System (WMS) and the Hydrologic Modelling System (HEC-HMS). The WMS was used to estimate the geometric parameters of the hydrographic basin from a digital elevation model and geographical information describing the location of the hydraulic infrastructure developed in the basin in recent years. The HEC-HMS was used to estimate the run-off hydrographs, by using historical rainfall data and calibrating the model with the observed hydrometric data. The lake bathymetry was taken into account in order to estimate the lake's water balance. Recent observations indicate that anthropogenic activities have modified the natural run-off features of the lake basin. The magnitude of these modifications was estimated by linking the WMS and HEC-HMS models. Application of these linked tools allowed the successful estimation of the modified basin limits and hydraulic behaviour of Lake Santa Ana.
The dynamics of water temperature, dissolved oxygen and total dissolved solids concentrations in Aguamilpa Reservoir was analysed by considering horizontal and water column variations. The reservoir model, CE-QUAL-W2, was used to simulate the temporal variations calibrated with data gathered every 2 months from June 2008 to June 2009. Temperature depth profiles indicated a typical asymmetry of reservoirs exhibiting a large stratification in the lower part near the dam. Dissolved oxygen concentration profiles exhibited some degree of anoxia in the bottom water during the rainy season (May through October). This is most likely due to decomposition vegetation and organic matter via soil erosion and runoff from the basin accumulating at the bottom of the reservoir. The reservoir stratification is clearly seasonal, occurring during the rainy season, especially in the lowest reservoir zones. The CE-QUAL-W2 model results provided a comprehensive understanding of the temporal behaviour of the study variables during the modelling study period. Application of this water quality model is directed to water resource managers to help them better understand the dynamics of physicochemical processes, and how they vary temporally and spatially in the reservoir, and to propose the best management practices for preserving or improving the water quality of the system.
A framework to publish simplified MODFLOW groundwater modeling capabilities to a web interface for use by water managers and stakeholders is presented. Numerical modeling simulations can assist aquifer management decisions, but the amount of time and professional expertise required to wield modern groundwater models often exceeds the resources of regulating agencieseven for simple modeling tasks that are repetitive in nature. The framework is capable of automating such modeling tasks, accepting user input, executing MODFLOW, and generating specialized results including maps and modeling reports. This framework was used to build a pilot system for an aquifer in central Utah, allowing a user to simulate the effects of proposed well diversions. This prototype system allows a user to input properties for any number of candidate wells, execute an associated MODFLOW model, and view drawdown contours and regions of decreased spring flow on a web map interface. The modeling analysis is cast into a geoprocessing workflow using ArcGIS and Arc Hydro Groundwater tools, and then made accessible from a server. Such automated and accessible modeling systems have promising potential to facilitate efficient groundwater resources management and reduce modeling errors.
The great demand for water resources from the Zarqa River Basin (ZRB) has resulted in a base-flow reduction of the River from 5 m 3 /s to less than 1 m 3 /s. This paper aims to predict Curve Numbers (CNs) as a baseline scenario and propose restoration scenarios for the ZRB. The method includes classifying the soil type and land use, predicting CNs, and proposing CN restoration scenarios. The prediction of existing CNs will be in parallel with the runoff prediction by using the US Army Corps of Engineers HEC-1 Model, and the Rainfall-Runoff Model (RRM). The models have been set up at the land use distribution of 0.3% water body, 9.3% forest and orchard, 71% mixture of grass, weeds, and desert shrubs, 7.0% crops, 4.0% urban areas, and 8.4% bare soil. The results show that CNs are 59, 78 and 89 under dry, normal and wet conditions, respectively. During the vegetation period, CNs are 52, 72 and 86 for dry, normal and wet conditions respectively. The restoration scenarios include how CNs decrease the runoff and increase the soil moisture when using the contours, terraces and crop residues. Analyzing the results of CN scenarios will be a fundamental tool in achieving watershed restoration targets.
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