WATERSHED WEIGHTING OF EXPORT COEFFICIENTS TO MAP CRITICAL PHOSPHOROUS LOADING AREAS1

ABSTRACT: The Export Coefficient model (ECM) is capable of generating reasonable estimates of annual phosphorous loading simply from a watershed's land cover data and export coefficient values (ECVs). In its current form, the ECM assumes that ECVs are homogeneous within each land cover type, yet basic nutrient runoff and hydrological theory suggests that runoff rates have spatial patterns controlled by loading and filtering along the flow paths from the upslope contributing area and downslope dispersal area. Using a geographic information system (GIS) raster, or pixel, modeling format, these contributing area and dispersal area (CADA) controls were derived from the perspective of each individual watershed pixel to weight the otherwise homogeneous ECVs for phosphorous. Although the CADA‐ECM predicts export coefficient spatial variation for a single land use type, the lumped basin load is unaffected by weighting. After CADA weighting, a map of the new ECVs addressed the three fundamental criteria for targeting critical pollutant loading areas: (1) the presence of the pollutant, (2) the likelihood for runoff to carry the pollutant offsite, and (3) the likelihood that buffers will trap nutrients prior to their runoff into the receiving water body. These spatially distributed maps of the most important pollutant management areas were used within New York's West Branch Delaware River watershed to demonstrate how the CADA‐ECM could be applied in targeting phosphorous critical loading areas.     

Weighting Nitrogen and Phosphorus Pixel Pollutant Loads to Represent Runoff and Buffering Likelihoods

Watershed models often estimate annual nitrogen (N) or phosphorus (P) pollutant loads in rural areas with export coefficient (EC) (kg/ha/yr) values based on land cover, and in urban areas as the product of spatially uniform event mean concentration (EMC) (mg/L) values and runoff volume. Actual N and P nonpoint source (NPS) pollutant loading has more spatial complexity due to watershed variation in runoff likelihood and buffering likelihood along surface and subsurface pathways, which can be represented in a contributing area dispersal area (CADA) NPS model. This research develops a CADA NPS model to simulate how watershed properties of elevation, land cover, and soils upslope and downslope of each watershed pixel influence nutrient loading. The model uses both surface and subsurface runoff indices (RI), and surface and subsurface buffer indices (BI), to quantify the runoff and buffering likelihood for each watershed pixel, and generate maps of weighted EC and EMC values that identify NPS pollutant loading hotspots. The research illustrates how CADA NPS model maps and pixel loading values are sensitive to the spatial resolution and accuracy of elevation and land cover data, and model predictions can represent the lower and upper bounds of NPS loading. The model provides managers with a tool to rapidly visualize, rank, and investigate likely areas of high nutrient export.     

Soils, water quality, and watershed size: interactions in the Maumee and Sandusky river basins of northwestern Ohio

Soil variability in watersheds accounts for the problem of partitioning downstream water quality data and evaluating sources of non-point pollution. This review of previous water quality studies was conducted to examine more closely the influence of soil properties on pollutant export. The approach used in this paper was to start with data from the two largest watersheds (Maumee and Sandusky) and then compare them on a unit area export basis with data from intermediate-size and smaller watersheds. General relationships between pollutant levels at the river mouth and upstream soil conditions are vague and seemingly contradictory at the large-watershed scale. With smaller watersheds, it can be determined that soil texture, slope, and internal drainage are controlling factors for pollutant export. Although Paulding (very-fine, illitic, nonacid, mesic Typic Epiaquept) and Roselms (very-fine, illitic, mesic Aeric Epiaqualf) soils occupy only 5% of the Maumee basin, they generate more than 10 times as much sediment per unit area as the tile-drained Hoytville (fine, illitic, mesic Mollic Epiaqualf) soils that occupy 16% of the Maumee basin. Tile drainage of very poorly drained soils that are formed from either glacial till or silty to sandy lake deposits reduces runoff and increases downward movement of soluble nutrients into tile drains. The assumption that sloping moraine areas are the primary source of pollutants should be reexamined based on this review.     

Modeling Watershed‐Scale Impacts of Stormwater Management with Traditional versus Low Impact Development Design

Stormwater runoff and associated pollutants from urban areas in the greater Chesapeake Bay Watershed (CBW) impair local streams and downstream ecosystems, despite urbanized land comprising only 7% of the CBW area. More recently, stormwater best management practices (BMPs) have been implemented in a low impact development (LID) manner to treat stormwater runoff closer to its source. This approach included the development of a novel BMP model to compare traditional and LID design, pioneering the use of comprehensively digitized storm sewer infrastructure and BMP design connectivity with spatial patterns in a geographic information system at the watershed scale. The goal was to compare total watershed pollutant removal efficiency in two study watersheds with differing spatial patterns of BMP design (traditional and LID), by quantifying the improved water quality benefit of LID BMP design. An estimate of uncertainty was included in the modeling framework by using ranges for BMP pollutant removal efficiencies that were based on the literature. Our model, using Monte Carlo analysis, predicted that the LID watershed removed approximately 78 kg more nitrogen, 3 kg more phosphorus, and 1,592 kg more sediment per square kilometer as compared with the traditional watershed on an annual basis. Our research provides planners a valuable model to prioritize watersheds for BMP design based on model results or in optimizing BMP selection.     

ESTIMATING NONPOINT SOURCE POLLUTION LOADS WITH A GIS SCREENING MODEL1

ABSTRACT: The St. Johns River Water Management District (SJR-WMD) is using a Geographic Information System (GIS) screening model to estimate annual nonpoint source pollution loads to surface waters and determine nonpoint source pollution problem areas within the SJRWMD. The model is a significant improvement over current practice because it is contained entirely within the district's GIS software, resulting in greater flexibility and efficiency, and useful visualization capabilities. Model inputs consist of five spatial data layers, runoff coefficients, mean runoff concentrations, and stormwater treatment efficiencies. The spatial data layers are: existing land use, future land use, soils, rainfall, and hydrologic boundaries. These data layers are processed using the analytical capabilities of a cell-based GIS. Model output consists of seven spatial data layers: runoff, total nitrogen, total phosphorous, suspended solids, biochemical oxygen demand, lead, and zinc. Model output can be examined visually or summarized numerically by drainage basin. Results are reported for only one of the SJRWMD's ten major drainage basins, the lower St. Johns River basin. The model was created to serve a major planning effort at the SJRWMD; results are being actively used to address nonpoint source pollution problems.     

MACROSCALE HYDROLOGIC MODELING FOR REGIONAL CLIMATE ASSESSMENT STUDIES IN THE SOUTHEASTERN UMTED STATES1

ABSTRACT: A macroscale hydrologic model is developed for regional climate assessment studies under way in the southeastern United States. The hydrologic modeling strategy is developed to optimize spatial representation of basin characteristics while maximizing computational efficiency. The model employs the “grouped response unit” methodology, which follows the natural drainage pattern of the area. First order streams are delineated and their surface characteristics are tested so that areas with statistically similar characteristics can be combined into larger computational zones for modeling purposes. Hydrologic response units (HRU) are identified within the modeling units and a simple three‐layer water balance model, Soil and Water Assessment Tool (SWAT), is executed for each HRU. The runoff values are then convoluted using a triangular unit hydrograph and routed by Muskingum‐Cunge method. The methodology is shown to produce accurate results relative to other studies, when compared to observations. The model is used to evaluate the potential error in hydrologic assessments when using GCM predictions as climatic input in a rainfall‐runoff dominated environment. In such areas, the results from this study, although limited in temporal and spatial scope, appear to imply that use of GCM climate predictions in short term quantitative analyses studies in rainfall‐runoff dominated environments should proceed with caution.     

POLLUTANT RUNOFF MODELS: SELECTION AND USE IN DECISION MAKING1

Models for pollutant runoff can be useful in water quality management planning if appropriately structured for the problem at hand. Accordingly, a “top-down” approach is proposed for the examination of extant pollutant runoff models. The approach consists of the identification of objectives and attributes that reflect the needs of planners and decision makers when these models are used for water quality management planning. Ideally, the attributes should concern the effect of model information on improved decision making and the cost of model application. Practical difficulties with the first attribute necessitates substitution of surrogate attributes reflecting model appropriateness, resolution, and uncertainty. Common pollutant runoff models, in particular export coefficients and hydrology-driven simulation models, are found to have serious weaknesses on some of the attribute scales. The “top-down” approach leads to a set of desirable pollutant runoff model attributes; alternate modeling techniques are thus examined in order to identify promising future directions for model development. The focus of this examination is phosphorus, due to its importance in the eutrophication of surface waters. Models for both sediment-attached and dissolved phosphorus are considered. Among the conclusions is the belief that the partial contributing area concept can yield an effective yet simple simulation despite the variable and complex nature of runoff.     

Diffuse pollution loading from urban stormwater runoff in Daejeon city, Korea

In this paper, stormwater runoff from an urban watershed with combined sewer systems located in Daejeon metropolitan city, Korea, was characterized to measure the stormwater runoff discharge rates and pollutant concentrations. The observed averaged event mean concentrations (EMCs) of combined sewer overflows (CSO) were 536.1mg TSS/L, 467.7 mg TCODcr/L, 142.7 mg TBOD/L, 16.5mg TN/L, and 13.5mg TP/L. A detention basin was proposed to reduce CSO, and its essential design elements were discussed. The first flush significantly affected contaminant constituents in the descending order of suspended solid>organics>nutrients. Storage volumes for containing the first flush to improve water quality of the receiving stream can be estimated based on the total suspended solid loading. In this study, detention of the first flush equivalent to 5mm of precipitation could reduce CSO-induced diffuse pollution loading to a receiving water body by up to 80% of the total suspended solid loading.     

MODELING URBAN NONPOINT SOURCE POLLUTION WITH A GEOGRAPHIC INFORMATION SYSTEM1

ABSTRACT: A geographic information system (GIS) was a useful aid in the assessment of urban nonpoint source pollution and the development of a pollution control strategy. The GIS was used for data integration and display, and to provide data for a nonpoint source model. An empirical nonpoint source loading model driven by land use was used to estimate pollutant loadings of priority pollutants. Pollutant loadings were estimated at fine spatial resolution and aggregated to storm sewer drainage basins (sewersheds). Eleven sewersheds were generated from digital versions of sewer maps. The pollutant loadings of individual land use polygons, derived as the units of analysis from street blocks, were aggregated to get total pollutant loadings within each sewershed. Based on the model output, a critical sewershed was located. Pollutant loadings at major sewer junctions within the critical sewershed were estimated to develop a mitigation strategy. Two approaches based on the installation of wet ponds were investigated - a regional approach using one large wet pond at the major sewer outfall and a multisite approach using a number of smaller sites for each major sewer junction. Cost analyses showed that the regional approach would be more cost effective, though it would provide less pollution control.     

Water Resources Modeling of the Ganges‐Brahmaputra‐Meghna River Basins Using Satellite Remote Sensing Data1

Nishat, Bushra and S.M. Mahbubur Rahman, 2009. Water Resources Modeling of the Ganges‐Brahmaputra‐Meghna River Basins Using Satellite Remote Sensing Data. Journal of the American Water Resources Association (JAWRA) 45(6):1313‐1327. Abstract: Large‐scale water resources modeling can provide useful insights on future water availability scenarios for downstream nations in anticipation of proposed upstream water resources projects in large international river basins (IRBs). However, model set up can be challenging due to the large amounts of data requirement on both static states (soils, vegetation, topography, drainage network, etc.) and dynamic variables (rainfall, streamflow, soil moisture, evapotranspiration, etc.) over the basin from multiple nations and data collection agencies. Under such circumstances, satellite remote sensing provides a more pragmatic and convenient alternative because of the vantage of space and easy availability from a single data platform. In this paper, we demonstrate a modeling effort to set up a water resources management model, MIKE BASIN, over the Ganges, Brahmaputra, and Meghna (GBM) river basins. The model is set up with the objective of providing Bangladesh, the lowermost riparian nation in the GBM basins, a framework for assessing proposed water diversion scenarios in the upstream transboundary regions of India and deriving quantitative impacts on water availability. Using an array of satellite remote sensing data on topography, vegetation, and rainfall from the transboundary regions, we demonstrate that it is possible to calibrate MIKE BASIN to a satisfactory level and predict streamflow in the Ganges and Brahmaputra rivers at the entry points of Bangladesh at relevant scales of water resources management. Simulated runoff for the Ganges and Brahmaputra rivers follow the trends in the rated discharge for the calibration period. However, monthly flow volume differs from the actual rated flow by (?) 8% to (+) 20% in the Ganges basin, by (?) 15 to (+) 12% in the Brahmaputra basin, and by (?) 15 to (+) 19% in the Meghna basin. Our large‐scale modeling initiative is generic enough for other downstream nations in IRBs to adopt for their own modeling needs.     

Assessing Surface Water Quality and Its Relation with Urban Land Cover Changes in the Lake Calumet Area, Greater Chicago

Urban land use and land cover change significantly affect spatial and temporal patterns of runoff, which in turn impacts surface water quality. With the exponential growth in urban areas over the past three decades, changes in land use and land cover to cater for the growth of cities has been a conspicuous spectacle in urban spaces. The main goal of this study was to assess the impacts of land cover change on runoff and surface water quality using a partial area hydrology framework. The study employed ArcHydro GIS extension and a modified version of Long-Term Hydrologic and Nonpoint Source Pollution model (L-THIA-NPS) in estimating runoff and nonpoint source pollutant concentration around Lake Calumet between 1992 and 2001. Data employed include National Land Cover Data set, rainfall data, digital elevation model (DEM), Soil Survey Geographic (SSURGO) data, and The United States Environmental Protection Agency’s STORET (storage and retrieval) water quality data. The model was able to predict surface water quality reasonably well over the study period. Sensitivity analysis facilitated a manual calibration of the model. Model validation was executed by comparing simulated results following calibration and observed water quality data for the study area. The study demonstrates that the level of concentration of nonpoint source pollutants in surface water within an urban watershed heavily depends on the spatiotemporal variations in areas that contribute towards runoff compared to the spatial extent of change in major land use/land cover.     

Development of a water quality loading index based on water quality modeling

Water quality modeling is an ideal tool for simulating physical, chemical, and biological changes in aquatic systems. It has been utilized in a number of GIS-based water quality management and analysis applications. However, there is considerable need for a decision-making process to translate the modeling result into an understandable form and thereby help users to make relevant judgments and decisions. This paper introduces a water quality index termed QUAL2E water quality loading index (QWQLI). This new WQI is based on water quality modeling by QUAL2E, which is a popular steady-state model for the water quality of rivers and streams. An experiment applying the index to the Sapgyo River in Korea was implemented. Unlike other WQIs, the proposed index is specifically used for simulated water quality using QUAL2E to mainly reflect pollutant loading levels. Based on the index, an iterative modeling-judgment process was designed to make decisions to decrease input pollutants from pollutant sources. Furthermore, an indexing and decision analysis can be performed in a GIS framework, which can provide various spatial analyses. This can facilitate the decision-making process under various scenarios considering spatial variability. The result shows that the index can evaluate and classify the simulation results using QUAL2E and that it can effectively identify the elements that should be improved in the decision-making process. In addition, the results imply that further study should be carried out to automate algorithms and subsidiary programs supporting the decision-making process.     

CALIBRATION OF STORM LOADS IN THE SOUTH PRONG WATERSHED,FLORIDA, USING BASINS/HSPF1

ABSTRACT: The South Prong watershed is a major tributary system of the Sebastian River and adjacent Indian River Lagoon. Continued urbanization of the Sebastian River drainage basin and other watersheds of the Indian River Lagoon is expected to increase runoff and nonpoint source pollutant loads. The St. Johns River Water Management District developed watershed simulation models to estimate potential impacts on the ecological systems of receiving waters and to assist planners in devising strategies to prevent further degradation of water resources. In the South Prong system, a storm water sampling program was carried out to calibrate the water quality components of the watershed model for total suspended solids (TSS), total phosphorous (TP), and total nitrogen (TN). During the period of May to November 1999, water quality and flow data were collected at three locations within the watershed. Two of the sampling stations were located at the downstream end of major watercourses. The third station was located at the watershed outlet. Five storm events were sampled and measured at each station. Sampling was conducted at appropriate intervals to represent the rising limb, peak, and recession limb of each storm event. The simulations were handled by HSPF (Hydrologic Simulation Program‐Fortran). Results include calibration of the hydrology and calibration of the individual storm loads. The hydrologic calibration was continuous over the period 1994 through 1999. Simulated storm runoff, storm loads, and event mean concentrations were compared with their corresponding observed values. The hydrologic calibration showed good results. The outcome of the individual storm calibrations was mixed. Overall, however, the simulated storm loads agreed reasonably well with measured loads for a majority of the storms.     

Dry Weather Water Quality Loadings in Arid,Urban Watersheds of the Los Angeles Basin,California, USA1

Abstract: Dry weather runoff in arid, urban watersheds may consist entirely of treated wastewater effluent and/or urban nonpoint source runoff, which can be a source of bacteria, nutrients, and metals to receiving waters. Most studies of urban runoff focus on stormwater, and few have evaluated the relative contribution and sources of dry weather pollutant loading for a range of constituents across multiple watersheds. This study assessed dry weather loading of nutrients, metals, and bacteria in six urban watersheds in the Los Angeles region of southern California to estimate relative sources of each constituent class and the proportion of total annual load that can be attributed to dry weather discharge. In each watershed, flow and water quality were sampled from storm drain and treated wastewater inputs, as well as from in‐stream locations during at least two time periods. Data were used to calculate mean concentrations and loads for various sources. Dry weather loads were compared with modeled wet weather loads under a range of annual rainfall volumes to estimate the relative contribution of dry weather load. Mean storm drain flows were comparable between all watersheds, and in all cases, approximately 20% of the flowing storm drains accounted for 80% of the daily volume. Wastewater reclamation plants (WRP) were the main source of nutrients, storm drains accounted for almost all the bacteria, and metals sources varied by constituent. In‐stream concentrations reflected major sources, for example nutrient concentrations were highest downstream of WRP discharges, while in‐stream metals concentrations were highest downstream of the storm drains with high metals loads. Comparison of wet vs. dry weather loading indicates that dry weather loading can be a significant source of metals, ranging from less than 20% during wet years to greater than 50% during dry years.     

Spatial Calibration and Temporal Validation of Flow for Regional Scale Hydrologic Modeling1

Abstract: Physically based regional scale hydrologic modeling is gaining importance for planning and management of water resources. Calibration and validation of such regional scale model is necessary before applying it for scenario assessment. However, in most regional scale hydrologic modeling, flow validation is performed at the river basin outlet without accounting for spatial variations in hydrological parameters within the subunits. In this study, we calibrated the model to capture the spatial variations in runoff at subwatershed level to assure local water balance, and validated the streamflow at key gaging stations along the river to assure temporal variability. Ohio and Arkansas‐White‐Red River Basins of the United States were modeled using Soil and Water Assessment Tool (SWAT) for the period from 1961 to 1990. R² values of average annual runoff at subwatersheds were 0.78 and 0.99 for the Ohio and Arkansas Basins. Observed and simulated annual and monthly streamflow from 1961 to 1990 is used for temporal validation at the gages. R² values estimated were greater than 0.6. In summary, spatially distributed calibration at subwatersheds and temporal validation at the stream gages accounted for the spatial and temporal hydrological patterns reasonably well in the two river basins. This study highlights the importance of spatially distributed calibration and validation in large river basins.     

Effects of Land‐Use and Land‐Cover Change on Evapotranspiration and Water Yield in China During 1900‐20001

Abstract: China has experienced a rapid land‐use/cover change (LUCC) during the 20th Century, and this process is expected to continue in the future. How LUCC has affected water resources across China, however, remains uncertain due to the complexity of LUCC‐water interactions. In this study, we used an integrated Dynamic Land Ecosystem Model (DLEM) in conjunction with spatial data of LUCC to estimate the LUCC effects on the magnitude, spatial and temporal variations of evapotranspiration (ET), runoff, and water yield across China. Through comparisons of DLEM results with other model simulations, field observations, and river discharge data, we found that DLEM model can adequately catch the spatial and seasonal patterns of hydrological processes. Our simulation results demonstrate that LUCC led to substantial changes in ET, runoff, and water yield in most of the China’s river basins during the 20th Century. The temporal and spatial patterns varied significantly across China. The largest change occurred during the second half century when almost all of the river basins had a decreasing trend in ET and an increasing trend in water yield and runoff, in contrast to the inclinations of ET and declinations of water yield in major river basins, such as Pearl river basin, Yangtze river basin, and Yellow river basin during the first half century. The increased water yield and runoff indicated alleviated water deficiency in China in the late 20th Century, but the increased peak flow might make the runoff difficult to be held by reservoirs. The continuously increasing ET and decreasing water yield in Continental river basin, Southwest river basin, and Songhua and Liaohe river basin implied regional water deficiency. Our study in China indicates that deforestation averagely increased ET by 138 mm/year but decreased water yield by the same amount and that reforestation averagely decreased ET by 422 mm/year since most of deforested land was converted to paddy land or irrigated cropland. In China, cropland‐related land transformation is the dominant anthropogenic force affecting water resources during the 20th Century. On national average, cropland expansion was estimated to increase ET by 182 mm/year while cropland abandonment decreased ET by 379 mm/year. Our simulation results indicate that urban sprawl generally decreased ET and increased water yield. Cropland managements (fertilization and irrigation) significantly increased ET by 98 mm/year. To better understand LUCC effects on China’s water resources, it is needed to take into account the interactions of LUCC with other environmental changes such as climate and atmospheric composition.     

A framework for assessing the impact of land use policy on community exposure to air toxics

Our research focuses on the linkage between land use planning policy and the spatial pattern of exposure to air toxics emissions. Our objective is to develop a modeling framework for assessment of the community health risk implications of land use policy. The modeling framework is not intended to be a regulatory tool for small-scale land use decisions, but a long-range planning tool to assess the community health risk implications of alternative land use scenarios at a regional or subregional scale. This paper describes the development and application of an air toxic source model for generating aggregate emission factors for industrial and commercial zoning districts as a function of permitted uses. To address the uncertainty of estimating air toxics emission rates for planned general land use or zoning districts, the source model uses an emissions probability mass function that weights each incremental permitted land use activity by the likelihood of occurrence. We thus reduce the uncertainty involved in planning for development with no prior knowledge of the specific industries that may locate within the land use district. These air toxics emission factors can then be used to estimate pollutant atmospheric mass flux from land use zoning districts, which can then be input to air dispersion and human health risk assessment models to simulate the spatial pattern of air toxics exposure risk. The model database was constructed using the California Air Toxics Inventory, 1997 US Economic Census, and land assessment records from several California counties. The database contains information on more than 200 air toxics at the 2-digit Standard Industrial Classification (SIC) level. We present a case study to illustrate application of the model. LUAIRTOX, the interactive spreadsheet model that applies our methodology to the California data, is available at http://www2.bren.ucsb.edu/~mwillis/LUAIRTOX.htm.     

A PLANNING METHOD FOR EVALUATING DOWNSTREAM EFFECTS OF DETENTION BASINS1

While storm water detention basins are widely used for controlling increases in peak discharges that result from urbanization, recent research has indicated that under certain circumstances detention storage can actually cause increases in peak discharge rates. Because of the potential for detrimental downstream effects, storm water management policies often require downstream effects to be evaluated. Such evaluation requires the design engineer to collect additional topographic and land use data and make costly hydrologic analyses. Thus, a method, which is easy to apply and which would indicate whether or not a detailed hydrologic analysis of downstream impacts is necessary, should decrease the average cost of storm water management designs. A planning method that does not require either a large data base or a computer is presented. The time co-ordinates of runoff hydrographs are estimated using the time-of-concentration and the SCS runoff curve number; the discharge coordinates are estimated using a simple peak discharge equation. While the planning method does not require a detailed design of the detention basin, it does provide a reasonably accurate procedure for evaluating whether or not the installation of a detention basin will cause adverse downstream flooding.     

SPATIAL VARIABILITY IN WATER‐BALANCE MODEL PERFORMANCE IN THE CONTERMINOUS UNITED STATES1

ABSTRACT: A monthly water‐balance (WB) model was tested in 44 river basins from diverse physiographic and climatic regions across the conterminous United States (U.S.). The WB model includes the concepts of climatic water supply and climatic water demand, seasonality in climatic water supply and demand, and soil‐moisture storage. Exhaustive search techniques were employed to determine the optimal set of precipitation and temperature stations, and the optimal set of WB model parameters to use for each basin. It was found that the WB model worked best for basins with: (1) a mean elevation less than 450 meters or greater than 2000 meters, and/or (2) monthly runoff that is greater than 5 millimeters (mm) more than 80 percent of the time. In a separate analysis, a multiple linear regression (MLR) was computed using the adjusted R‐square values obtained by comparing measured and estimated monthly runoff of the original 44 river basins as the dependent variable, and combinations of various independent variables [streamflow gauge latitude, longitude, and elevation; basin area, the long‐term mean and standard deviation of annual precipitation; temperature and runoff; and low‐flow statistics (i.e., the percentage of months with monthly runoff that is less than 5 mm)]. Results from the MLR study showed that the reliability of a WB model for application in a specific region can be estimated from mean basin elevation and the percentage of months with gauged runoff less than 5 mm. The MLR equations were subsequently used to estimate adjusted R‐square values for 1,646 gauging stations across the conterminous U.S. Results of this study indicate that WB models can be used reliably to estimate monthly runoff in the eastern U.S., mountainous areas of the western U.S., and the Pacific Northwest. Applications of monthly WB models in the central U.S. can lead to uncertain estimates of runoff.     

Evaluation of the MIKE SHE Model for Application in the Loess Plateau,China1

Abstract: Quantifying the hydrologic responses to land use/land cover change and climate variability is essential for integrated sustainable watershed management in water limited regions such as the Loess Plateau in Northwestern China where an adaptive watershed management approach is being implemented. Traditional empirical modeling approach to quantifying the accumulated hydrologic effects of watershed management is limited due to its complex nature of soil and water conservation practices (e.g., biological, structural, and agricultural measures) in the region. Therefore, the objective of this study was to evaluate the ability of the distributed hydrologic model, MIKE SHE to simulate basin runoff. Streamflow data measured from an overland flow‐dominant watershed (12 km²) in northwestern China were used for model evaluation. Model calibration and validation suggested that the model could capture the dominant runoff process of the small watershed. We found that the physically based model required calibration at appropriate scales and estimated model parameters were influenced by both temporal and spatial scales of input data. We concluded that the model was useful for understanding the rainfall‐runoff mechanisms. However, more measured data with higher temporal resolution are needed to further test the model for regional applications.