Evaluation of the Temporal Transferability of a Model Describing Dissolved Solids in Streams of the Upper Colorado River Basin1

Kenney, Terry A. and Susan G. Buto, 2012. Evaluation of the Temporal Transferability of a Model Describing Dissolved Solids in Streams of the Upper Colorado River Basin. Journal of the American Water Resources Association (JAWRA) 48(5): 1041‐1053. DOI: 10.1111/j.1752‐1688.2012.00667.x Abstract: The application of a nonlinear least‐squares regression model describing the sources and transport of dissolved solids in streams of the Upper Colorado River Basin, and that was calibrated using data from water year 1991, was evaluated for use in predicting annual dissolved‐solids loads for the years 1974 through 1998. Simulations for each water year were run using annual climate data. To evaluate how well the model captures the observed annual variability across the basin, differences in predicted annual dissolved‐solids loads for each simulated year and 1991 were compared with differences in monitored annual loads. The temporal trend of the differences between predicted annual loads for the simulated years and the load for 1991 generally followed the trend of the monitored loads. The model appears to underpredict the largest annual loads and overpredict some of the smaller annual loads. An underprediction bias for wetter years was evident in the residuals as was an overprediction bias, to a lesser degree, for drier years. A regression analysis on the residuals suggests that the underprediction bias is associated with precipitation differences from 1991 and with previously defined downward trends in dissolved‐solids concentrations in the basin. In general, given the representative climatic conditions, the model adequately performs throughout the period examined. However, the model is most transferable to years with climatic conditions similar to 1991.     

Predicting Debris Yield From Burned Watersheds: Comparison of Statistical and Artificial Neural Network Models1

Abstract: Alluvial fans in southern California are continuously being developed for residential, industrial, commercial, and agricultural purposes. Development and alteration of alluvial fans often require consideration of mud and debris flows from burned mountain watersheds. Accurate prediction of sediment (hyper‐concentrated sediment or debris) yield is essential for the design, operation, and maintenance of debris basins to safeguard properly the general population. This paper presents results based on a statistical model and Artificial Neural Network (ANN) models. The models predict sediment yield caused by storms following wildfire events in burned mountainous watersheds. Both sediment yield prediction models have been developed for use in relatively small watersheds (50‐800 ha) in the greater Los Angeles area. The statistical model was developed using multiple regression analysis on sediment yield data collected from 1938 to 1983. Following the multiple regression analysis, a method for multi‐sequence sediment yield prediction under burned watershed conditions was developed. The statistical model was then calibrated based on 17 years of sediment yield, fire, and precipitation data collected between 1984 and 2000. The present study also evaluated ANN models created to predict the sediment yields. The training of the ANN models utilized single storm event data generated for the 17‐year period between 1984 and 2000 as the training input data. Training patterns and neural network architectures were varied to further study the ANN performance. Results from these models were compared with the available field data obtained from several debris basins within Los Angeles County. Both predictive models were then applied for hind‐casting the sediment prediction of several post 2000 events. Both the statistical and ANN models yield remarkably consistent results when compared with the measured field data. The results show that these models are very useful tools for predicting sediment yield sequences. The results can be used for scheduling cleanout operation of debris basins. It can be of great help in the planning of emergency response for burned areas to minimize the damage to properties and lives.     

Modeled Sources,Transport, and Accumulation of Dissolved Solids in Water Resources of the Southwestern United States1

Anning, David W., 2011. Modeled Sources, Transport, and Accumulation of Dissolved Solids in Water Resources of the Southwestern United States. Journal of the American Water Resources Association (JAWRA) 47(5):1087‐1109. DOI: 10.1111/j.1752‐1688.2011.00579.x Abstract: Information on important source areas for dissolved solids in streams of the southwestern United States, the relative share of deliveries of dissolved solids to streams from natural and human sources, and the potential for salt accumulation in soil or groundwater was developed using a SPAtially Referenced Regressions On Watershed attributes model. Predicted area‐normalized reach‐catchment delivery rates of dissolved solids to streams ranged from <10 (kg/year)/km² for catchments with little or no natural or human‐related solute sources in them to 563,000 (kg/year)/km² for catchments that were almost entirely cultivated land. For the region as a whole, geologic units contributed 44% of the dissolved‐solids deliveries to streams and the remaining 56% of the deliveries came from the release of solutes through irrigation of cultivated and pasture lands, which comprise only 2.5% of the land area. Dissolved‐solids accumulation is manifested as precipitated salts in the soil or underlying sediments, and (or) dissolved salts in soil‐pore or sediment‐pore water, or groundwater, and therefore represents a potential for aquifer contamination. Accumulation rates were <10,000 (kg/year)/km² for many hydrologic accounting units (large river basins), but were more than 40,000 (kg/year)/km² for the Middle Gila, Lower Gila‐Agua Fria, Lower Gila, Lower Bear, Great Salt Lake accounting units, and 247,000 (kg/year)/km² for the Salton Sea accounting unit.     

Comparison of Measured and MM5 Modeled Meteorology Data for Simulating Flow in a Mountain Watershed1

Herr, Joel W., Krish Vijayaraghavan, and Eladio Knipping, 2010. Comparison of Measured and MM5 Modeled Meteorology Data for Simulating Flow in a Mountain Watershed. Journal of the American Water Resources Association (JAWRA) 46(6):1255–1263. DOI: 10.1111/j.1752-1688.2010.00489.x Abstract: Accurate simulation of time-varying flow in a river system depends on the quality of meteorology inputs. The density of meteorology measurement stations can be insufficient to capture spatial heterogeneity of precipitation, especially in mountainous areas. The Watershed Analysis Risk Management Framework (WARMF) model was applied to the Catawba River watershed of North and South Carolina to simulate flow and water quality in rivers and a series of 11 reservoirs. WARMF was linked with the AMSTERDAM air model to analyze the water quality benefit from reduced atmospheric emissions. The linkage requires accurate simulation of meteorology for all seasons and for all types of precipitation events. WARMF was driven by the mesoscale meteorology model MM5 processed by the Meteorology Chemistry Interface Processor, which provides greater spatial density but less accuracy than meteorology stations. WARMF was also run with measured data from the National Climatic Data Center (NCDC) to compare the performance of the watershed model using measured data vs. modeled meteorology as input. A one year simulation using MM5 modeled meteorology performed better overall than the simulation using NCDC data for the volumetric water balance measure used for calibration, but MM5 represented precipitation from a dissipated hurricane poorly, which propagated into errors of simulated flow.