Developing Subseasonal to Seasonal Climate Forecast Products for Hydrology and Water Management

We describe a new effort to enhance climate forecast relevance and usability through the development of a system for evaluating and displaying real‐time subseasonal to seasonal (S2S) climate forecasts on a watershed scale. Water managers may not use climate forecasts to their full potential due to perceived low skill, mismatched spatial and temporal resolutions, or lack of knowledge or tools to ingest data. Most forecasts are disseminated as large‐domain maps or gridded datasets and may be systematically biased relative to watershed climatologies. Forecasts presented on a watershed scale allow water managers to view forecasts for their specific basins, thereby increasing the usability and relevance of climate forecasts. This paper describes the formulation of S2S climate forecast products based on the Climate Forecast System version 2 (CFSv2) and the North American Multi‐Model Ensemble (NMME). Forecast products include bi‐weekly CFSv2 forecasts, and monthly and seasonal NMME forecasts. Precipitation and temperature forecasts are aggregated spatially to a United States Geological Survey (USGS) hydrologic unit code 4 (HUC‐4) watershed scale. Forecast verification reveals appreciable skill in the first two bi‐weekly periods (Weeks 1–2 and 2–3) from CFSv2, and usable skill in NMME Month 1 forecast with varying skills at longer lead times dependent on the season. Application of a bias‐correction technique (quantile mapping) eliminates forecast bias in the CFSv2 reforecasts, without adding significantly to correlation skill.     

Evaluation of the Global Precipitation Measurement (GPM) Satellite Rainfall Products over the Lower Colorado River Basin,Texas

Quality of precipitation products from the Integrated Multi‐satellitE Retrievals for Global Precipitation Measurement mission (IMERG) was evaluated over the Lower Colorado River Basin of Texas. Observations of several rainfall events of a wide range of magnitudes during May 2015 by a very dense network of 241 rain gauges over the basin were used as a reference. The impact of temporal and spatial downscaling of different satellite products (near/post‐real‐time) on their accuracy was studied. Generally, all IMERG products perform better when the temporal and spatial resolutions are downscaled. The Final product shows relatively better performance compared to the near‐real‐time products in terms of basic performance measures; however, regarding rainfall detection, all products show nearly similar performance. When considering rainfall detection, IMERG adequately captures the precipitation events; however, in terms of spatial patterns and accuracy, more improvements are needed. IMERG products analysis results may help developers gain insight into the regional performance of the product, improve the product algorithms, and provide information to end users on the products’ suitability for potential hydrometeorological applications. Overall, the IMERG products, even the uncalibrated product at its finest resolution, showed reasonable performance indicating their great potential for applications such as water resources management, prevention of natural disasters, and flood forecasting.     

A Calibrated,High‐Resolution GOES Satellite Solar Insolation Product for a Climatology of Florida Evapotranspiration1

Paech, Simon J., John R. Mecikalski, David M. Sumner, Chandra S. Pathak, Quinlong Wu, Shafiqul Islam, and Taiye Sangoyomi, 2009. A Calibrated, High‐Resolution GOES Satellite Solar Insolation Product for a Climatology of Florida Evapotranspiration. Journal of the American Water Resources Association (JAWRA) 45(6):1328‐1342. Abstract: Estimates of incoming solar radiation (insolation) from Geostationary Operational Environmental Satellite observations have been produced for the state of Florida over a 10‐year period (1995‐2004). These insolation estimates were developed into well‐calibrated half‐hourly and daily integrated solar insolation fields over the state at 2 km resolution, in addition to a 2‐week running minimum surface albedo product. Model results of the daily integrated insolation were compared with ground‐based pyranometers, and as a result, the entire dataset was calibrated. This calibration was accomplished through a three‐step process: (1) comparison with ground‐based pyranometer measurements on clear (noncloudy) reference days, (2) correcting for a bias related to cloudiness, and (3) deriving a monthly bias correction factor. Precalibration results indicated good model performance, with a station‐averaged model error of 2.2 MJ m^?2/day (13%). Calibration reduced errors to 1.7 MJ m^?2/day (10%), and also removed temporal‐related, seasonal‐related, and satellite sensor‐related biases. The calibrated insolation dataset will subsequently be used by state of Florida Water Management Districts to produce statewide, 2‐km resolution maps of estimated daily reference and potential evapotranspiration for water management‐related activities.     

Satellite Precipitation Measurements for Water Resource Monitoring1

Abstract: Satellites offer an unrivaled vantage point to observe and measure Earth system processes and parameters. Observations of meteorological phenomena permit a more holistic view of the weather and climate that is not possible through conventional surface observations. Precipitation (rain and snow) in particular, benefit from such observations since precipitation is spatially and temporally highly variable: conventional gauge and radar measurements tend to be land‐based with variable coverage. This paper provides an overview of the satellite systems that provide the observations, the techniques used to derive precipitation from the observations, and examples of the precipitation products available for users to access.     

Estimation of Evapotranspiration Across the Conterminous United States Using a Regression With Climate and Land‐Cover Data1

Sanford, Ward E. and David L. Selnick, 2012. Estimation of Evapotranspiration Across the Conterminous United States Using a Regression with Climate and Land‐Cover Data. Journal of the American Water Resources Association (JAWRA) 1‐14. DOI: 10.1111/jawr.12010 Abstract: Evapotranspiration (ET) is an important quantity for water resource managers to know because it often represents the largest sink for precipitation (P) arriving at the land surface. In order to estimate actual ET across the conterminous United States (U.S.) in this study, a water‐balance method was combined with a climate and land‐cover regression equation. Precipitation and streamflow records were compiled for 838 watersheds for 1971‐2000 across the U.S. to obtain long‐term estimates of actual ET. A regression equation was developed that related the ratio ET/P to climate and land‐cover variables within those watersheds. Precipitation and temperatures were used from the PRISM climate dataset, and land‐cover data were used from the USGS National Land Cover Dataset. Results indicate that ET can be predicted relatively well at a watershed or county scale with readily available climate variables alone, and that land‐cover data can also improve those predictions. Using the climate and land‐cover data at an 800‐m scale and then averaging to the county scale, maps were produced showing estimates of ET and ET/P for the entire conterminous U.S. Using the regression equation, such maps could also be made for more detailed state coverages, or for other areas of the world where climate and land‐cover data are plentiful.     

PRECIPITATION CHANGES FROM 1956 TO 1996 ON THE WALNUT GULCH EXPERIMENTAL WATERSHED1

ABSTRACT: The climate of Southern Arizona is dominated by summer precipitation, which accounts for over 60 percent of the annual total. Summer and non‐summer precipitation data from the USDA‐ARS Walnut Gulch Experimental Watershed are analyzed to identify trends in precipitation characteristics from 1956 to 1996. During this period, annual precipitation increased. The annual precipitation increase can be attributed to an increase in precipitation during non‐summer months, and is paralleled by an increase in the proportion of annual precipitation contributed during non‐summer months. This finding is consistent with previously reported increases in non‐summer precipitation in the southwestern United States. Detailed event data were analyzed to provide insight into the characteristics of precipitation events during this time period. Precipitation event data were characterized based on the number of events, event precipitation amount, 30‐minute event intensity, and event duration. The trend in non‐summer precipitation appears to be a result of increased event frequency since the number of events increased during nonsummer months, although the average amount per event, average event intensity, and average event duration did not. During the summer “monsoon” season, the frequency of recorded precipitation events increased but the average precipitation amount per event decreased. Knowledge of precipitation trends and the characteristics of events that make up a precipitation time series is a critical first step in understanding and managing water resources in semiarid ecosystems.     

Assessing the Impact of Areal Precipitation Input on Streamflow Simulations Using the SWAT Model1

Masih Ilyas, Shreedhar Maskey, Stefan Uhlenbrook, and Vladimir Smakhtin, 2011. Assessing the Impact of Areal Precipitation Input on Streamflow Simulations Using the SWAT Model. Journal of the American Water Resources Association (JAWRA) 47(1):179‐195. DOI: 10.1111/j.1752‐1688.2010.00502.x Abstract: Reduction of input uncertainty is a challenge in hydrological modeling. The widely used model Soil Water Assessment Tool (SWAT) uses the data of a precipitation gauge nearest to the centroid of each subcatchment as an input for that subcatchment. This may not represent overall catchment precipitation conditions well. This paper suggests an alternative – using areal precipitation obtained through interpolation. The effectiveness of this alternative is evaluated by comparing its simulations with those based on the standard SWAT precipitation input procedure. The model is applied to mountainous semiarid catchments in the Karkheh River basin, Iran. The model performance is evaluated at daily, monthly, and annual scales by using a number of performance indicators at 15 streamflow gauging stations each draining an area in the range of 590‐42,620 km². The comparison suggests that the use of areal precipitation improves model performance particularly in small subcatchments in the range of 600‐1,600 km². The modified areal precipitation input results in increased reliability of simulated streamflows in the areas of low rain gauge density. Both precipitation input methods result in reasonably good simulations for larger catchments (over 5,000 km²). The use of areal precipitation input improves the accuracy of simulated streamflows with spatial resolution and density of rain gauges having significant impact on results.     

Precipitation as the Primary Driver of Variability in River Nitrogen Loads in the Midwest United States

Nitrogen (N) losses from agricultural lands in the Midwest United States are contributing to the expansion of the hypoxic zone in the Gulf of Mexico. This study evaluated the importance of inter‐annual variability in precipitation, land cover, and N fertilizer use on NO₃ + NO₂‐N loads in seven United States Midwestern Rivers using the backward stepwise regression analysis. At the annual scale, fluctuations in the current and previous years’ precipitations explained much of the variation in streamflow, baseflow, and N‐load. Previous years precipitation effects were associated with fillable soil porosity. In some years, higher residual soil N from previous dry years also contributed to an increase in N‐load. Area under soybean production (SOY), a surrogate for replacement of prairies and small grains was generally not a significant explanatory variable. Fertilizer use from 1987 to 2012 was also not a significant explanatory variable in the annual analysis. Precipitation in both the current and previous months and previous year were important in explaining variation in monthly streamflow, baseflow, and N‐load. SOY was significant in one or two months from June to August, but had a higher p‐value than precipitation. We conclude recent increases in river N‐loads are primarily due to wet climate and minimally due to the changes in land cover or N fertilizer use. Under current cropping systems and agronomic N application rates, tile water remediation will be necessary to reduce river N‐loads.     

Assessment of the TRMM 3B42 Precipitation Product in Southern Brazil

The increase in the use of satellite‐derived precipitation products generated by different methods and algorithms emphasizes the need for a deeper analysis of their quality and accuracy. Using the contingency table method, we evaluated the accuracy of versions 6 and 7 of the Tropical Rainfall Measuring Mission Precipitation (TRMM) 3B42 product in southern Brazil by comparing daily precipitation over 13 years (V6 was tested for historical context). The interpolated data from 25 rain gauges were compared with both versions of TRMM. The V7 product tended to produce a slight increase in PC (proportion correct). V7 also showed a slight increase in the correlation coefficient (CC) and a significant increase in the H (hit rate) and CSI (critical success) indexes. However, the upgraded version shows an undesirable increase in the false alarm ratio. When the rainfall volumes were compared, V6 clearly underestimated the total rainfall over the entire period, but the V7 product slightly overestimated the cumulative volume (11%) which still represented a more reliable estimate than from V6. Furthermore, the main improvement in V7 was a large increase in the quantitative recognition of extreme precipitation events: V6 detected only 1% of the daily rainfalls above 60 mm, whereas V7 detected 57% of the events.     

The Influence of Forest Regrowth on the Stream Discharge in the North Carolina Piedmont Watersheds

This study focuses on the relationships of watershed runoff with historical land use/land cover (LULC) and climate trends. Over the 20th Century, LULC in the Southeast United States, particularly the North Carolina Piedmont, has evolved from an agriculture dominated to an extensively forested landscape with more recent localized urbanization. The regrowth of forest has an important influence on the hydrology of the region as it enhances ecosystem interaction with recent climate change. During 1920‐2009, the amount of precipitation in some parts of the North Carolina Piedmont forest regrowth area showed increasing trends without corresponding increments in runoff. We employed the Soil and Water Assessment Tool (SWAT) to backcast long‐term hydrologic behavior of watersheds in North Carolina with different LULC conditions: (1) LULC conversion from agricultural to forested area and (2) long‐term stable forested area. Comparing U.S. Geological Survey‐measured stream discharge with SWAT‐simulated stream discharge under the assumption of constant 2006 LULC, we found significant stream discharge underprediction by SWAT in two LULC conversion watersheds during the early simulation period (1920s) with differences gradually decreasing by the mid‐1970s. This model bias suggests that forest regrowth on abandoned agricultural land was a key factor contributing to mitigate the impact of increased precipitation on runoff due to increasing water consumption driven by changes in vegetation.     

Estimating Floodwater Depths from Flood Inundation Maps and Topography

Information on flood inundation extent is important for understanding societal exposure, water storage volumes, flood wave attenuation, future flood hazard, and other variables. A number of organizations now provide flood inundation maps based on satellite remote sensing. These data products can efficiently and accurately provide the areal extent of a flood event, but do not provide floodwater depth, an important attribute for first responders and damage assessment. Here we present a new methodology and a GIS‐based tool, the Floodwater Depth Estimation Tool (FwDET), for estimating floodwater depth based solely on an inundation map and a digital elevation model (DEM). We compare the FwDET results against water depth maps derived from hydraulic simulation of two flood events, a large‐scale event for which we use medium resolution input layer (10 m) and a small‐scale event for which we use a high‐resolution (LiDAR; 1 m) input. Further testing is performed for two inundation maps with a number of challenging features that include a narrow valley, a large reservoir, and an urban setting. The results show FwDET can accurately calculate floodwater depth for diverse flooding scenarios but also leads to considerable bias in locations where the inundation extent does not align well with the DEM. In these locations, manual adjustment or higher spatial resolution input is required.     

Assessing Satellite and Ground‐Based Potential Evapotranspiration for Hydrologic Applications in the Colorado River Basin

This study evaluates a remotely sensed and two ground‐based potential evapotranspiration (PET) products for hydrologic application in the Upper Colorado River Basin (UCRB). The remotely sensed Moderate Resolution Imaging Spectroradiometer product (MODIS‐PET) is a continuous, daily time series with 250 m resolution derived using the Priestley‐Taylor (P‐T) equation. The MODIS‐PET is evaluated against regional flux tower data as well as a synthetic pan product (Epan; 0.125°, daily) derived from the North American Land Data Assimilation System (NLDAS) and a Hargreaves PET derived from DAYMET variables (DAYMET‐PET; 1 km, daily). Compared to point‐scale PET computed using regional flux tower data, the MODIS‐PET had lower errors, with RMSE values ranging from 2.24 to 2.85 mm/day. Epan RMSE values ranged from 3.70 to 3.76 mm/day and DAYMET‐PET RMSE values ranged from 3.55 to 4.58 mm/day. Further investigation showed biases in temperature and radiation data contribute to uncertainty in the MODIS‐PET values, while bias in NLDAS temperature, downward shortwave (SW↓), and downward longwave (LW↓) propagate in the Epan estimates. Larger discrepancies between methods were observed in the warmer, drier regions of the UCRB, however, the MODIS‐PET was more responsive to landcover transitions and better captured basin heterogeneity. Results indicate the satellite‐based MODIS product can serve as a viable option for obtaining spatial PET values across the UCRB.     

Comparison and Evaluation of Gridded Precipitation Datasets in a Kansas Agricultural Watershed Using SWAT

Gridded precipitation datasets are becoming a convenient substitute for gauge measurements in hydrological modeling; however, these data have not been fully evaluated across a range of conditions. We compared four gridded datasets (Daily Surface Weather and Climatological Summaries [DAYMET], North American Land Data Assimilation System [NLDAS], Global Land Data Assimilation System [GLDAS], and Parameter‐elevation Regressions on Independent Slopes Model [PRISM]) as precipitation data sources and evaluated how they affected hydrologic model performance when compared with a gauged dataset, Global Historical Climatology Network‐Daily (GHCN‐D). Analyses were performed for the Delaware Watershed at Perry Lake in eastern Kansas. Precipitation indices for DAYMET and PRISM precipitation closely matched GHCN‐D, whereas NLDAS and GLDAS showed weaker correlations. We also used these precipitation data as input to the Soil and Water Assessment Tool (SWAT) model that confirmed similar trends in streamflow simulation. For stations with complete data, GHCN‐D based SWAT‐simulated streamflow variability better than gridded precipitation data. During low flow periods we found PRISM performed better, whereas both DAYMET and NLDAS performed better in high flow years. Our results demonstrate that combining gridded precipitation sources with gauge‐based measurements can improve hydrologic model performance, especially for extreme events.     

A METHODOLOGY FOR EVALUATING DEVELOPMENT-ENVIRONMENTAL CONFLICTS ON WILD AND SCENIC RIVERS1

ABSTRACT: A methodology is developed for examining the environmental and developmental conflicts inherent in the classification process of a wild river. The Salmon River in Idaho is used as an example of the methodology. The steps were: 1. a resource inventory, 2. an evaluation methodology, and 3. an economic comparison of resource use tradeoffs. Alternatives for the Salmon were examined, following generally the procedures outlined in the United States Water Resources Council's Establishment of Principles and Standards for Planning Water and Related Land Resources Final comparisons showed that hydroelectric development had greater net benefits than outdoor recreation at up to a three percent recreation growth rate. When recreation use grew at a faster rate, recreation had a considerable margin of net benefits in its favor.     

Error Autocorrelation and Linear Regression for Temperature‐Based Evapotranspiration Estimates Improvement1

Medeiros, Patrick Valverde, Francisco Fernando Noronha Marcuzzo, Cristián Youlton, and Edson Wendland, 2012. Error Autocorrelation and Linear Regression for Temperature‐Based Evapotranspiration Estimates Improvement. Journal of the American Water Resources Association (JAWRA) 48(2): 297‐305. DOI: 10.1111/j.1752‐1688.2011.00614.x Abstract: Estimates of evapotranspiration on a local scale is important information for agricultural and hydrological practices. However, equations to estimate potential evapotranspiration based only on temperature data, which are simple to use, are usually less trustworthy than the Food and Agriculture Organization (FAO)‐Penman‐Monteith standard method. The present work describes two correction procedures for potential evapotranspiration estimates by temperature, making the results more reliable. Initially, the standard FAO‐Penman‐Monteith method was evaluated with a complete climatologic data set for the period between 2002 and 2006. Then temperature‐based estimates by Camargo and Jensen‐Haise methods have been adjusted by error autocorrelation evaluated in biweekly and monthly periods. In a second adjustment, simple linear regression was applied. The adjusted equations have been validated with climatic data available for the Year 2001. Both proposed methodologies showed good agreement with the standard method indicating that the methodology can be used for local potential evapotranspiration estimates.     

Development of Sediment and Nutrient Export Coefficients for U.S. Ecoregions

Water quality impairment due to excessive nutrients and sediment is a major problem in the United States (U.S.). An important step in the mitigation of impairment in any given water body is determination of pollutant sources and amount. The sheer number of impaired waters and limited resources makes simplistic load estimation methods such as export coefficient (EC) methods attractive. Unfortunately ECs are typically based on small watershed monitoring data, which are very limited and/or often based on data collected from distant watersheds with drastically different conditions. In this research, we seek to improve the accuracy of these nutrient export estimation methods by developing a national database of localized EC for each ecoregion in the U.S. A stochastic sampling methodology loosely based on the Monte‐Carlo technique was used to construct a database of 45 million Soil and Water Assessment Tool (SWAT) simulations. These simulations consider a variety of climate, topography, soils, weather, land use, management, and conservation implementation conditions. SWAT model simulations were successfully validated with edge‐of‐field monitoring data. Simulated nutrient ECs compared favorably with previously published studies. These ECs may be used to rapidly estimate nutrient loading for any small catchment in the U.S. provided the location, area, and land‐use distribution are known.     

Spatiotemporal Variability of Modeled Watershed Scale Surface‐Depression Storage and Runoff for the Conterminous United States

This study explores the viability of using simulated monthly runoff as a proxy for landscape‐scale surface‐depression storage processes simulated by the United States Geological Survey’s National Hydrologic Model (NHM) infrastructure across the conterminous United States (CONUS). Two different temporal resolution model codes (daily and monthly) were run in the NHM with the same spatial discretization. Simulated values of daily surface‐depression storage (treated as a decimal fraction of maximum volume) as computed by the daily Precipitation‐Runoff Modeling System (NHM‐PRMS) and normalized runoff (0 to 1) as computed by the Monthly Water Balance Model (NHM‐MWBM) were aggregated to monthly and annual values for each hydrologic response unit (HRU) in the CONUS geospatial fabric (HRU; n = 109,951) and analyzed using Spearman’s rank correlation test. Correlations between simulated runoff and surface‐depression storage aggregated to monthly and annual values were compared to identify where which time scale had relatively higher correlation values across the CONUS. Results show Spearman’s rank values >0.75 (highly correlated) for the monthly time scale in 28,279 HRUs (53.35%) compared to the annual time scale in 41,655 HRUs (78.58%). The geographic distribution of HRUs with highly correlated monthly values show areas where surface‐depression storage features are known to be common (e.g., Prairie Pothole Region, Florida).     

Evaluation of Short-to-Medium Range Streamflow Forecasts Obtained Using an Enhanced Version of SRM1

Harshburger, Brian J., Karen S. Humes, Von P. Walden, Brandon C. Moore, Troy R. Blandford, and Albert Rango, 2010. Evaluation of Short-to-Medium Range Streamflow Forecasts Obtained Using an Enhanced Version of SRM. Journal of the American Water Resources Association (JAWRA) 46(3):603-617. DOI: 10.1111/j.1752-1688.2010.00437.x Abstract: As demand for water continues to escalate in the western United States, so does the need for accurate streamflow forecasts. Here, we describe a methodology for generating short-to-medium range (1 to 15 days) streamflow forecasts using an enhanced version of the Snowmelt Runoff Model (SRM), snow-covered area data derived from MODIS products, data from Snow Telemetry stations, and meteorological forecasts. The methodology was tested on three mid-elevation, snowmelt-dominated basins ranging in size from 1,600 to 3,500 km². To optimize the model performance and aid in its operational implementation, two enhancements have been made to SRM: (1) the use of an antecedent temperature index method to track snowpack cold content, and (2) the use of both maximum and minimum critical temperatures to partition precipitation into rain, snow, or a mixture of rain and snow. The comparison of retrospective model simulations with observed streamflow shows that the enhancements significantly improve the model performance. Streamflow forecasts generated using the enhanced version of the model compare well with the observed streamflow for the earlier leadtimes; forecast performance diminishes with leadtime due to errors in the meteorological forecasts. The three basins modeled in this research are typical of many mid-elevation basins throughout the American West, thus there is potential for this methodology to be applied successfully to other mountainous basins.     

Efficient and Practical Approaches to Ground‐Water Right Transfers Under the Prior Appropriation Doctrine and the Snake River Example1

Abstract: Water right transfers are one of the basic means of implementing changes in water use in the highly appropriated water resource systems of the western United States. Many of these systems are governed by the Prior Appropriation Doctrine, which was not originally intended for application to ground‐water pumping and the conjunctive management of ground water and surface water, and thus creates an administrative challenge. That challenge results from the fact that ground‐water pumping can affect all interconnected surface‐water bodies and the effects may be immeasurably small relative to surface water discharge and greatly attenuated in time. Although we may have the ability to calculate the effects of ground‐water pumping and transfers of pumping location on surface‐water bodies, mitigating for all the impacts of each individual transfer is sufficiently inefficient that it impedes the transfer process, frustrates water users, and consequently inhibits economic development. A more holistic approach to ground‐water right transfers, such as a ground‐water accounting or banking scheme, may adequately control transfer third‐party effects while reducing mitigation requirements on individual transfers. Acceptance of an accounting scheme can accelerate the transfer process, and possibly reduce the administrative burden.