Case Studies of a MODIS-Based Potential Evapotranspiration Input to the Sacramento Soil Moisture Accounting Model

A satellite-based potential evapotranspiration (PET) estimate derived from Moderate Resolution Imaging Spectroradiometer (MODIS) observations was tested for input to the spatially lumped and gridded Sacramento Soil Moisture Accounting (SAC-SMA) model. The 15 forecast points within the National Weather Service (NWS) North Central River Forecast Center (NCRFC) forecasting region were the basis for this analysis. Through a series of case studies, the MODIS-derived PET estimate (M-PET) was evaluated for input to the SAC-SMA model by comparing streamflow simulations with those from traditional SAC-SMA evapotranspiration (ET) demand. Two prior studies have evaluated the M-PET data 1) to compute new long-term average ET demand values and 2) to input a time series (i.e., daily time-varying PET) to the NWS Hydrology Laboratory–Research Distributed Hydrologic Model (HL-RDHM), a spatially distributed version of the SAC-SMA model. This current paper presents results from a third test in which the M-PET time series is input to the lumped SAC-SMA model. In all cases, evaluation is between the M-PET data and the long-term average values used by the NWS. Similar to prior studies, results of the current analysis are mixed with improved model evaluation statistics for 4 of 15 basins tested. Of the three cases, using the time-varying M-PET as input to the distributed SAC-SMA model led to the most promising results, with model simulations that are at least as good as those when using the SAC-SMA ET demand. Analyses of the model-simulated ET suggest that the time-varying M-PET input may produce a more physically realistic representation of ET processes in both the lumped and distributed versions of the SAC-SMA model

Evapotranspiration Estimates Derived Using Multi-Platform Remote Sensing in a Semiarid Region

Evapotranspiration (ET) is a key component of the water balance, especially in arid and semiarid regions. The current study takes advantage of spatially-distributed, near real-time information provided by satellite remote sensing to develop a regional scale ET product derived from remotely-sensed observations. ET is calculated by scaling PET estimated from Moderate Resolution Imaging Spectroradiometer (MODIS) products with downscaled soil moisture derived using the Soil Moisture Ocean Salinity (SMOS) satellite and a second order polynomial regression formula. The MODis-Soil Moisture ET (MOD-SMET) estimates are validated using four flux tower sites in southern Arizona USA, a calibrated empirical ET model, and model output from Version 2 of the North American Land Data Assimilation System (NLDAS-2). Validation against daily eddy covariance ET indicates correlations between 0.63 and 0.83 and root mean square errors (RMSE) between 40 and 96 W/m2. MOD-SMET estimates compare well to the calibrated empirical ET model, with a −0.14 difference in correlation between sites, on average. By comparison, NLDAS-2 models underestimate daily ET compared to both flux towers and MOD-SMET estimates. Our analysis shows the MOD-SMET approach to be effective for estimating ET. Because it requires limited ancillary ground-based data and no site-specific calibration, the method is applicable to regions where ground-based measurements are not available

Distributed Hydrologic Modeling Using Satellite-Derived Potential Evapotranspiration

Satellite-derived potential evapotranspiration (PET) estimates computed from Moderate Resolution Imaging Spectroradiometer (MODIS) observations and the Priestley-Taylor formula (M-PET) are evaluated as input to the Hydrology Laboratory Research Distributed Hydrologic Model (HL-RDHM). The HL-RDHM is run at a 4-km spatial and 6-h temporal resolution for 13 watersheds in the upper Mississippi and Red River basins for 2003-10. Simulated discharge using inputs of daily M-PET is evaluated for all watersheds, and simulated evapotranspiration (ET) is evaluated at two watersheds using nearby latent heat flux observations. M-PET-derived model simulations are compared to output using the long-term average PET values (default-PET) provided as part of theHL-RDHMapplication. In addition, uncalibrated and calibrated simulations are evaluated for both PET data sources. Calibrating select model parameters is found to substantially improve simulated discharge for both datasets. Overall average percent bias (PBias) and Nash-Sutcliffe efficiency (NSE) values for simulated discharge are better from the default-PET than the M-PET for the calibrated models during the verification period, indicating that the time-varying M-PET input did not improve the discharge simulation in theHL-RDHM. M-PET tends to produce higher NSE values than the default-PET for the Wisconsin and Minnesota basins, but lower NSE values for the Iowa basins. M-PET-simulated ET matches the range and variability of observed ET better than the default-PET at two sites studied and may provide potential model improvements in that regard

Adapting Urban Water Systems to Manage Scarcity in the 21st Century: The Case of Los Angeles.

Acute water shortages for large metropolitan regions are likely to become more frequent as climate changes impact historic precipitation levels and urban population grows. California and Los Angeles County have just experienced a severe four year drought followed by a year of high precipitation, and likely drought conditions again in Southern California. We show how the embedded preferences for distant sources, and their local manifestations, have created and/or exacerbated fluctuations in local water availability and suboptimal management. As a socio technical system, water management in the Los Angeles metropolitan region has created a kind of scarcity lock-in in years of low rainfall. We come to this through a decade of coupled research examining landscapes and water use, the development of the complex institutional water management infrastructure, hydrology and a systems network model. Such integrated research is a model for other regions to unpack and understand the actual water resources of a metropolitan region, how it is managed and potential ability to become more water self reliant if the institutions collaborate and manage the resource both parsimoniously, but also in an integrated and conjunctive manner. The Los Angeles County metropolitan region, we find, could transition to a nearly water self sufficient system

The Effect of Wildfire on Soil Mercury Concentrations in Southern California Watersheds

Mercury (Hg) stored in vegetation and soils is known to be released to the atmosphere during wildfires, increasing atmospheric stores and altering terrestrial budgets. Increased erosion and transport of sediments is well-documented in burned watersheds, both immediately post-fire and as the watershed recovers; however, understanding post-fire mobilization of soil Hg within burned watersheds remains elusive. The goal of the current study is to better understand the impact of wildfire on soil-bound Hg during the immediate post-fire period as well as during recovery, in order to assess the potential for sediment-driven transport to and within surface waters in burned watersheds. Soils were collected from three southern California watersheds of similar vegetation and soil characteristics that experienced wildfire. Sampling in one of these watersheds was extended for several seasons (1.5 years) in order to investigate temporal changes in soil Hg concentrations. Laboratory analysis included bulk soil total Hg concentrations and total organic carbon of burned and unburned samples. Soils were also fractionated into a subset of grain sizes with analysis of Hg on each fraction. Low Hg concentrations were observed in surface soils immediately post-fire. Accumulation of Hg coincident with moderate vegetative recovery was observed in the burned surface soils 1 year following the fire, and mobilization was also noted during the second winter (rainy) season. Hg concentrations were highest in the fine-grained fraction of unburned soils; however, in the burned soils, the distribution of soil-bound Hg was less influenced by grain size. The accelerated accumulation of Hg observed in the burned soils, along with the elevated risk of erosion, could result in increased delivery of organic- or particulate-bound Hg to surface waters in post-fire systems

A multi-criteria evaluation of land-surface models and application to semi-arid regions

Soil-Vegetation-Atmosphere-Transfer Schemes (SVATS) are used in global climate studies to simulate and help understand the complex interactions between the climate and the biosphere. There currently exists a multitude of SVATS of varying complexity differing in terms of the modeled physics and the manner and sophistication with which the processes are represented. This analysis uses systems-based multi-criteria techniques to investigate the performance and sensitivity of various SVATS and their parameters. Results indicate that, once complexity reaches a certain level, incorporating more physics does not necessarily result in improved simulations or reduced errors and that several parameters in the models are insensitive regardless of the input data (i.e., vegetation type). To better understand SVATS performance in semi-arid regions, and to evaluate the various impacts of data on the parameter estimation problem, an intensive calibration and validation study is undertaken. Findings show that calibrated parameters result in improved performance over default, proxy site parameters result in similar performance for many time periods, and there is a need to include wet periods with elevated latent heat to capture the variability of climatic conditions such as the monsoon and El Nino winters. Last, a preliminarily investigation of the performance of the BATS2 model is undertaken to evaluate the capabilities to simulate carbon (along with energy and water) fluxes in semi-arid regions. Results show poor performance for carbon flux simulations and that improvements are needed to better represent C4 vegetation for semi-acid regions. Future research will be directed toward integrated modeling (carbon, energy, and water) in semi-arid regions

Analysis of the National Weather Service soil moisture accounting models for flood prediction in the northeast floods of January 1996

Extensive flooding occurred throughout the northeastern United States during January of 1996. The flood event cost the lives of 33 people and over a billion dollars in flood damage. Following the "Blizzard of '96", a warm front moved into the Mid Atlantic region bringing extensive rainfall and causing significant melting and flooding to occur. Flood forecasting is a vital part of the National Weather Service (NWS) hydrologic responsibilities. Currently, the NWS River Forecast Centers use either the Antecedent Precipitation Index (API) or the Sacramento Soil-Moisture Accounting Model (SAC-SMA). This study evaluates the API and SAC-SMA models for their effectiveness in flood forecasting during this rain-on-snow event. The SAC-SMA, in conjunction with the SNOW-17 model, is calibrated for five basins in the Mid-Atlantic region using the Shuffled Complex Evolution (SCE-UA) automatic algorithm developed at the University of Arizona. Nash-Sutcliffe forecasting efficiencies (Er) for the calibration period range from 0. 79 to 0.87, with verification values from 0.42 to 0.95. Flood simulations were performed on the five basins using the API and calibrated SAC SMA model. The SAC-SMA model does a better job of estimating observed flood discharge on three of the five study basins, while two of the basins experience flood simulation problems with both models. Study results indicate the SAC-SMA has the potential for better flood forecasting during complex rain-on-snow events such as during the January 1996 floods in the Northeast.Digitized from paper copies provided by the Department of Hydrology & Atmospheric Sciences

Predicting the Impacts of Urbanization on Basin-scale Runoff and Infiltration in Semi-arid Regions

The current study was undertaken to improve the understanding of the long-term impacts of urbanization on hydrologic behavior and water supply in semi-arid regions. The study focuses on the Upper Santa Clara River basin in northern Los Angeles County which is undergoing rapid and extensive development. The Hydrologic Simulation Program- Fortran (HSPF) model is parameterized with land use, soil, and channel characteristics of the study watershed. Model parameters related to hydrologic processes are calibrated at the daily timestep using various spatial configurations of precipitation and parameters. Results indicate that the HSPF performs best with distributed precipitation forcing and parameters (distributed scenario), however the model performs fairly well under all scenarios. The model also shows slightly better performance during wetter seasons and years than during drier periods. Potential urbanization scenarios are generated on the basis of a regional development plan. The calibrated (and validated) model is run under the proposed development scenarios for a ten year period. Results reveal that increasing development increases total annual runoff and wet season flows, while decreases are observed in baseflow and groundwater recharge during both dry and wet seasons. As development increases, medium sized storms increase in both peak flow and overall volume, while low and high flow events (extremes) appear less affected. Urbanization is also shown to decrease recharge and, when considered at the regional-scale, could potentially result in a loss of critical water supply to southern California

Predicting the Impacts of Urbanization on Basin-scale Runoff and Infiltration in Semi-arid Regions

The current study was undertaken to improve the understanding of the long-term impacts of urbanization on hydrologic behavior and water supply in semi-arid regions. The study focuses on the Upper Santa Clara River basin in northern Los Angeles County which is undergoing rapid and extensive development. The Hydrologic Simulation Program- Fortran (HSPF) model is parameterized with land use, soil, and channel characteristics of the study watershed. Model parameters related to hydrologic processes are calibrated at the daily timestep using various spatial configurations of precipitation and parameters. Results indicate that the HSPF performs best with distributed precipitation forcing and parameters (distributed scenario), however the model performs fairly well under all scenarios. The model also shows slightly better performance during wetter seasons and years than during drier periods. Potential urbanization scenarios are generated on the basis of a regional development plan. The calibrated (and validated) model is run under the proposed development scenarios for a ten year period. Results reveal that increasing development increases total annual runoff and wet season flows, while decreases are observed in baseflow and groundwater recharge during both dry and wet seasons. As development increases, medium sized storms increase in both peak flow and overall volume, while low and high flow events (extremes) appear less affected. Urbanization is also shown to decrease recharge and, when considered at the regional-scale, could potentially result in a loss of critical water supply to southern California