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The article presents a response from the authors to a commentary about their paper on a direct geomorphologic instantaneous unit hydrograph model for runoff estimation in ungauged watersheds, and discusses the semiarid characteristics of the Golpayegan watershed.

We present an urban runoff model designed for stormwater managers to quantify runoff reduction benefits of mitigation actions that has lower input data and user expertise requirements than most commonly used models. The stormwater tool to estimate load reductions (TELR) employs a semi-distributed approach, where landscape characteristics and process representation are spatially-lumped within urban catchments on the order of 100 acres (40 ha). Hydrologic computations use a set of metrics that describe a 30-year rainfall distribution, combined with well-tested algorithms for rainfall-runoff transformation and routing to generate average annual runoff estimates for each catchment. User inputs include the locations and specifications for a range of structural best management practice (BMP) types. The model was tested in a set of urban catchments within the Lake Tahoe Basin of California, USA, where modeled annual flows matched that of the observed flows within 18% relative error for 5 of the 6 catchments and had good regional performance for a suite of performance metrics. Comparisons with continuous simulation models showed an average of 3% difference from TELR predicted runoff for a range of hypothetical urban catchments. The model usually identified the dominant BMP outflow components within 5% relative error of event-based measured flow data and simulated the correct proportionality between outflow components. TELR has been implemented as a web-based platform for use by municipal stormwater managers to inform prioritization, report program benefits and meet regulatory reporting requirements ( www.swtelr.com ). [ABSTRACT FROM AUTHOR]

The importance of the mean annual runoff (MAR)-hydrological variable is paramount for catchment planning, development and management. MAR depicts the amount of uncertainty or chaos (implicitly information content) of the catchment. The uncertainty associated with MAR of quaternary catchments (QCs) in the Upper Vaal catchment of South Africa has been quantified through Shannon entropy. As a result of chaos over a period of time, the hydrological catchment behavior/response in terms of MAR could be characterized by its resilience. Uncertainty (chaos) in QCs was used as a surrogate measure of catchment resilience. MAR data on surface water resources (WR) of South Africa of 1990 (i.e., WR90), 2005 (WR2005) and 2012 (W2012) were used in this study. A linear zoning for catchment resilience in terms of water resources sustainability was defined. Regression models (with high correlation) between the relative changes/variations in MAR data sets and relative changes in entropy were established, for WR2005 and WR2012. These models were compared with similar relationships for WR90 and WR2005, previously reported. The MAR pseudo-elasticity of the uncertainty associated with MAR was derived from regression models to characterize the resilience state of QCs. The MAR pseudo-elasticity values were relatively small to have an acceptable level of catchment resilience in the Upper Vaal catchment. Within the resilience zone, it was also shown that the effect of mean annual evaporation (MAE) was negatively significant on MAR pseudo-elasticity, compared to the effect of mean annual precipitation (MAP), which was positively insignificant. [ABSTRACT FROM AUTHOR]

The results of modeling of the long-term fluctuations in Lake Baikal levels and Angara River runoff are presented. The dynamic-stochastical model was developed and used to obtain analytical relationships between the statistic characteristics of the Baikal levels fluctuations and the parameters of forcing processes, including water inflow into the lake and the effective evaporation from its surface. The parameter λ determining the inertia of the Baikal levels fluctuations, decreased by about three times after Irkutsk Reservoir filling, resulting in an increase in the variance of the lake levels fluctuations. The dependence of variances of the Baikal levels fluctuations and Angara runoff on parameter λ was studied. It is shown that the decreasing in the variance of the Baikal levels fluctuations corresponds to increasing in the variance of Angara river runoff and vice versa. The results of numerical modeling of Baikal levels fluctuations show that water withdrawal from inflow into the lake has an adverse effect on Angara runoff regime. [ABSTRACT FROM AUTHOR]

Rainfall–runoff models with different conceptual structures for the hydrological processes can be calibrated to effectively reproduce the hydrographs of the total runoff, while resulting in water budget components that are essentially different. This finding poses an open question on the reliability of rainfall–runoff models in reproducing hydrological components other than those used for calibration. In an effort to address this question, we use data from the Glafkos catchment in western Greece to calibrate and compare the ENNS model, a research-oriented lumped model developed for the river Enns in Austria developed for the river Enns in Austria, with the operational MIKE SHE model. Model performance is assessed in the light of the conceptual/structural differences of the modelled hydrological processes, using indices calculated independently for each year, rather than for the whole calibration period, since the former are stricter. We show that even small differences in the representation of hydrological processes may impact considerably on the water budget components that are not measured (i.e. not used for model calibration). From all water budget components, direct runoff exhibits the highest sensitivity to structural differences and related model parameters.EDITOR M.C. AcremanASSOCIATE EDITOR S. Huang [ABSTRACT FROM AUTHOR]

Correct determination of direct runoff is crucial for proper and safe dimensioning of hydroengineering structures. It is commonly assessed using SCS-CN method developed in the United States. However, due to deficiencies of this method, many improvements and modifications have been proposed. In this paper, a modified Sahu-Mishra-Eldo (SME) method was introduced and tested for three catchments located in the upper Vistula basin. Modification of SME method involved a determination of maximum potential retention S based on CN parameter derived from SCS-CN method. The modified SME method yielded direct runoff values very similar to those observed in the investigated catchments. Moreover, it generated significantly smaller errors in the direct runoff estimation as compared with SCS-CN and SME methods in the analyzed catchments. This approach may be used for estimating the runoff in uncontrolled catchments. [ABSTRACT FROM AUTHOR]

Variations in riverine solute chemistry with changing runoff are used to interrogate catchment hydrology and to investigate chemical reactions in Earth's critical zone. This approach requires some understanding of how spatial and temporal averaging of solute-generating reactions affect the dissolved load of rivers and streams. In this study, we investigate the concentration-runoff (C-Q) dynamics of a suite of major (Na, Mg, Ca, Si, K, and SO4) and trace (Al, Ba, Cd, Co, Cr, Cu, Fe, Ge, Li, Mn, Mo, Nd, Ni, Rb, Sr, U, V, and Zn) elements in nested catchments of variable size, spanning the geomorphic gradient from the Andes Mountains to the Amazon Foreland-floodplain. The major elements exhibit various degrees of dilution with increasing runoff at all sites, whereas the concentrations of most trace elements either increase or show no relationship with increasing runoff in the three larger catchments (160-28,000 km2 area). We show that the observed main stem C-Q dynamics are influenced by variable mixing of tributaries with distinct C-Q relationships. Trace element C-Q relationships are more variable among tributaries relative to major elements, which could be the result of variations in geomorphology, lithology, and hydrology of the subcatchments. Certain trace metals are also lost from solution during in-channel processes (possibly related to colloidal size-partitioning), which may exert an additional control on C-Q dynamics. Overall, we suggest that tributary aggregation effects should be assessed in heterogeneous catchments before C-Q or ratio-Q relationships can be interpreted as reflecting catchment-wide solute generation processes and their relationship to hydrology. [ABSTRACT FROM AUTHOR]

The western interior portions of Puerto Rico offer optimal climatic conditions for coffee cultivation. However, land and water degradation result when abrupt topographic relief and high annual rainfall combine with forest conversion for coffee farming. Small-scale rainfall simulation experiments were conducted to quantify runoff and erosion from four land surface types (i.e., mulched, weed-covered, and bare soils under active cultivation, and unpaved roads) representative of coffee farms in Puerto Rico. Results show that mulch-covered soils had runoff coefficients similar to those from undisturbed forested conditions (~4%), and that they eroded at rates about a quarter of those for bare cultivated soils. Weed-covered soils had surprisingly high runoff coefficients (~70%), yet their erosion rates were only three-fourths of those for bare soils. Annualized erosion rates from unpaved roads were 65 Mg ha−1 y−1, or ten times greater than bare soils and about a hundred times higher than weed- or mulch-covered surfaces. Farm-scale sediment production estimates amount to ~11 Mg ha−1 y−1, about two-orders of magnitude higher than under forested conditions. At the farm-scale, only 2 - 8% of the total sediment is potentially attributable to cultivated hillslopes. In contrast, unpaved roads may account for over 90% of the sediment budget, even though they comprise only 15% of the farm surface area. Therefore, while providing mulch or a vegetative cover to bare cultivated soils should be part of effective soil management, mitigating the effects of coffee cultivation on downstream water resources must focus on the unpaved road network as the primary sediment source. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The objective of this research is to reduce scale effects on surface runoff routing processes in coarse-resolution hydrologic models to produce event hydrograph characteristics (peak and timing) similar to those obtained from fine-resolution models. Herein, this concept is referred to as upscaling. The developed upscaling approach combines statistical and physics-based techniques and is applied to the Ohio River Basin using a synthetic 2-year, 24-h runoff experiment. Cumulative distribution functions (CDFs) for surface flow path travel times based on 90-m-resolution digital elevation model (DEM) data and conceptualized model units representing individual catchments in a model are matched by adjusting surface roughness along simulated hillslopes. The travel time CDF for individual catchments based on 90-m DEM data are approximated using the beta distribution to facilitate applications in large watersheds. Nine model resolutions are considered: 1 (reference model resolution), 3.2, 10, 32, 100, 320, 1,000, 3,200, and 10;000 km2, where model resolution corresponds to the threshold area used to define the underlying river network and catchment boundaries. Simulated hydrographs at the outlet for the eight coarser model resolutions have peak discharges and times to peak that are similar to those obtained from the reference model resolution. To match hydrograph characteristics, surface roughness along the hillslope flow paths are adjusted by, on average, -85 to þ94%, where the positive values are for the 3.2-km2 resolution and the largest reductions are for the 10,000-km2 resolution. [ABSTRACT FROM AUTHOR]

In one of the widely used methods to estimate surface runoff - Soil Conservation Service Curve Number (SCS-CN), the antecedent moisture condition (AMC) is categorized into three AMC levels causing irrational abrupt jumps in estimated runoff. A few improved SCS-CN methods have been developed to overcome several in-built inconsistencies in the soil moisture accounting (SMA) procedure that lies behind the SCS-CN method. However, these methods still inherit the structural inconsistency in the SMA procedure. In this study, a modified SCS-CN method was proposed based on the revised SMA procedure incorporating storm duration and a physical formulation for estimating antecedent soil moisture ( V ). The proposed formulation for V estimation has shown a high degree of applicability in simulating the temporal pattern of soil moisture in the experimental plot. The modified method was calibrated and validated using a dataset of 189 storm-runoff events from two experimental watersheds in the Chinese Loess Plateau. The results indicated that the proposed method, which boosted the model efficiencies to 88% in both calibration and validation cases, performed better than the original SCS-CN and the Singh et al. (2015) method, a modified SCS-CN method based on SMA. The proposed method was then applied to a third watershed using the tabulated CN value and the parameters of the minimum infiltration rate ( f ) and coefficient ( β) derived for the first two watersheds. The root mean square error between the measured and predicted runoff values was improved from 6 mm to 1 mm. Moreover, the parameter sensitivity analysis indicated that the potential maximum retention ( S) parameter is the most sensitive, followed by f . It can be concluded that the modified SCS-CN method, may predict surface runoff more accurately in the Chinese Loess Plateau. [ABSTRACT FROM AUTHOR]

Newly developed approaches based on satellite altimetry and gravity measurements provide promising results on glacier dynamics in the Pamir-Himalaya but cannot resolve short-term natural variability at regional and finer scale. We contribute to the ongoing debate by upscaling a hydrological model that we calibrated for the central Pamir. The model resolves the spatiotemporal variability in runoff over the entire catchment domain with high efficiency. We provide relevant information about individual components of the hydrological cycle and quantify short-term hydrological variability. For validation, we compare the modeled total water storages (TWS) with GRACE (Gravity Recovery and Climate Experiment) data with a very good agreement where GRACE uncertainties are low. The approach exemplifies the potential of GRACE for validating even regional scale hydrological applications in remote and hard to access mountain regions. We use modeled time series of individual hydrological components to characterize the effect of climate variability on the hydrological cycle. We demonstrate that glaciers play a twofold role by providing roughly 35% of the annual runoff of the Panj River basin and by effectively buffering runoff both during very wet and very dry years. The modeled glacier mass balance (GMB) of −0.52 m w.e. yr−1 (2002-2013) for the entire catchment suggests significant reduction of most Pamiri glaciers by the end of this century. The loss of glaciers and their buffer functionality in wet and dry years could not only result in reduced water availability and increase the regional instability, but also increase flood and drought hazards. [ABSTRACT FROM AUTHOR]

Stormwater runoff poses serious environmental problems and public health issues in Rwanda, a tropical country that is increasingly suffering from severe floods, landslides, soil erosion and water pollution. Using the WetSpa Extension model, this study assessed the changes in rainfall runoff depth in Rwanda from 1990 to 2016 in response to precipitation and land use changes. Our results show that Rwanda has experienced a significant conversion of natural forest and grassland to cropland and built-up areas. During the period 1990-2016, 7090.02 km2 (64.5%) and 1715.26 km2 (32.1%) of forest and grassland covers were lost, respectively, while the cropland and built-up areas increased by 135.3% (8503.75 km2) and 304.3% (355.02 km2), respectively. According to our estimates, the land use change effect resulted in a national mean runoff depth increase of 2.33 mm/year (0.38%). Although precipitation change affected the inter-annual fluctuation of runoff, the long-term trend of runoff was dominated by land use change. The top five districts that experienced the annual runoff depth increase (all >3.8 mm/year) are Rubavu, Nyabihu, Ngororero, Gakenke, and Musanze. Their annual runoff depths increased at a rate of >3.8 mm/year during the past 27 years, due to severe deforestation (ranging from 62% to 85%) and cropland expansion (ranging from 123% to 293%). These areas require high priority in runoff control using terracing in croplands and rainwater harvesting systems such as dam/reservoirs, percolation tanks, storage tanks, etc. The wet season runoff was three times higher than the dry season runoff in Rwanda; appropriate rainwater management and reservation could provide valuable irrigation water for the dry season or drought years (late rainfall onsets or early rainfall cessations). It was estimated that a reservation of 30.5% (3.99 km3) of the runoff in the wet season could meet the cropland irrigation water gap during the dry season in 2016. [ABSTRACT FROM AUTHOR]

During cruise 65 of the R/V Akademik Mstislav Keldysh in the Kara Sea, three transects were executed: one eastwards from the Novaya Zemlya Archipelago and two in the St. Anna and Voronin troughs. It was noted that the continental runoff affected the entire surveyed aquatic area, even at the northern extremity of the Novaya Zemlya Archipelago. The transect along the St. Anna Trough showed the presence of a slope frontal zone overlaid at the surface by a desalinated layer. The Voronin Trough was characterized by sliding of slope waters. The hydrochemical parameters show that the surveys were carried out during a recession of biological activity of the waters and that the peak bloom was over by that time. The hydrochemical structure of waters conformed to early autumn conditions, but before the beginning of intense cooling of surface waters. [ABSTRACT FROM AUTHOR]

• In fingerprinting method sampling from only the influent of a WWTP is required. • Fingerprinting method is based on the rain proportion in a sample and a mass balance. • Drugs like painkillers are suitable tracers for estimating the rain proportion. The ecological state of receiving water bodies can be significantly influenced by organic micropollutants that are emitted via stormwater runoff. Reported efforts to quantify the emission of micropollutants mainly focus on sampling at combined sewer overflows and storm sewer outfalls, which can be challenging. An alternative method, called fingerprinting, was developed and tested in this study. The fingerprinting method utilizes wastewater treatment plant (WWTP) influent samples and derives the proportion of stormwater in a sample. This is achieved by comparing the wet weather vs dry weather concentrations of substances-tracers which are present only in wastewater. It is then possible to estimate the concentration of organic micropollutants in stormwater runoff from measurements in the influent of a WWTP based on a mass balance. In this research, the fingerprinting method was applied in influent samples obtained in five WWTPs in the Netherlands. In total, 28 DWF and 22 WWF samples were used. The chosen tracers were ibuprofen, 2-hydroxyibuprofen, naproxen and diclofenac. Subsequently, the concentration in stormwater runoff of 403 organic micropollutants was estimated via the WWF samples. The substances that were present and analyzed included glyphosate and AMPA, 24 out of 254 pesticides, 6 out of 28 organochlorine pesticides, 45 out of 63 pharmaceuticals, 15 out of 15 PAHs, 2 of the 7 PCBs, and 20 of 33 other substances (e.g. bisphenol-A). A comparison with findings from other studies suggested that the fingerprinting method yields trustworthy results. It was also noted that a representative and stable dry weather flow reference concentration is a strict requirement for the successful application of the proposed method. [Display omitted] [ABSTRACT FROM AUTHOR]

• Preferential flow induced by dynamic changes of desiccation cracks (PF-DC) was simulated using four different models. • A full dynamic dual-permeability model (DDPM) was necessary to accurately simulate PF-DC. • Models neglecting cracks or dynamic of desiccation cracks are not recommended to simulate PF-DC. • A lighter DDPM only considering crack evolution can tentatively substitute the DDPM in specific cases. • Uncertainties of shrinking-swelling parameters showed the smallest errors with respect to simplified models. Quantitative investigation on the preferential flow induced by desiccation cracks (PF-DC) remains a great challenge due to the soil shrinking-swelling behavior. This work presents a series of comparative numerical studies to investigate the accuracy and substitutability of different models in simulating the water flux, hydrological response and crack evolution induced by PF-DC. As a comparative study, an effective dynamic dual-permeability model (DDPM) we recently developed and validated was regarded as a benchmark model. Three numerical experiments were conducted to (i) compare the difference among the single-domain model (SDM), rigid dual-permeability model (RDPM) and DDPM; (ii) test the sensitivity of the DDPM to the shrinking-swelling parameters; (iii) test the rationality of a "lighter" dynamic DPM (LDPM) only considering the proportion changes of each domain while neglecting the variation of hydraulic properties. The results showed that compared to the DDPM, the SDM overestimated the water content under low-rainfall intensity while underestimating the water content under high-intensity rainfall and failed to capture the early increase of water content in deep soils induced by PF-DC. The RDPM greatly overestimated the total water content and water storage capacity of the crack domain, which was not suggested to be used in the surface runoff or flood forecast. The DDPM is overall not sensitive to the shrinking-swelling parameters, indicative of relatively loose accuracy requirements in measuring the soil shrinking-swelling parameters. The LDPM can be a tentative alternative option for the DDPM, but it is better not to use it to evaluate the surface runoff or use it under long-term extreme drought. In conclusion, the prediction errors without considering crack evolution and variation of hydraulic properties of each domain (RDPM) are the highest, then followed by the only considering crack evolution (LDPM) and uncertainties of shrinking-swelling parameters. [ABSTRACT FROM AUTHOR]

A procedure has been developed for the prediction of heavy metal concentrations in storm rainfall in St. Petersburg on the assumption of equal rates of metal influx with precipitations to the Baltic Sea and St. Petersburg territory. The concentrations of mercury, copper, and zinc in stormwater runoff from different administrative districts of the city have been calculated, and the predicted values have been compared with those determined experimentally. [ABSTRACT FROM AUTHOR]

Many watershed studies rely on pressure transducers to measure and report stream and groundwater levels in order to characterize the hydrology of the region. The accuracy of pressure transducers in some applications have recently been questioned in studies reporting artificially exaggerated high or low pressure readings that cannot be explained by daily hydrological fluctuations. In a watershed field investigation, data analyses have revealed, for some sensors, patterns of artificial changes in stream and groundwater levels as a function of water and atmospheric temperature. These patterns do not follow the expected variation that could be caused by natural phenomena (i.e. changes in head caused by evapotranspiration). Laboratory analyses of temperature-induced artificial pressure changes reproduces this error and yielded functional relationships for thermal artifact corrections. Using these relationships, stream and groundwater levels can be back-calculated yielding a more accurate watershed hydrologic characterization. By removing the thermal artifacts from laboratory and field data, errors are reduced by up to 65% (laboratory) and 81% (field data). The developed procedure can be used in other settings where pressure transducers are used, such as studies in rainfall/runoff variations, runoff measurements in urban settings, and the impacts of new development in rural watersheds. [ABSTRACT FROM AUTHOR]

By tracking the feature displacement between satellite images spaced approximately one year apart, surface runoff has been shown to have a long-term impact on the average ice flow of a land-terminating sector of Greenland. In this study, we revisit the multi-year trends in ice flow by assessing more carefully the impact of seasonal fluctuation in velocity on the annual mean ice velocity. We find that, depending on the length and period used to measure displacement, seasonal fluctuations do have an impact on observed velocities on up to 15%, and can affect decadal trends. Nevertheless, the magnitude of this fluctuation is small enough to confirm the general slowdown observed during the 2000–2012 period. Between 2012 and 2019, we find significant re-acceleration of low-lying glaciers tongue but velocity trends elsewhere are generally insignificant and not spatially consistent. Finally, we propose a more selective approach to recovering velocity trends using satellite imagery that involves using only measurements where the image pair starting date is before summer, in order to have comparable measurements for every year, sampling a melt season and the following winter. [Display omitted] • Starting date of image pairs for feature-tracking impacts ice velocities up to 15%. • We still find decelerating ice velocity trend over 2000–2012 in Southwest Greenland. • We do not find a significant reaccelerating trend for 2012–2019 as pre-viously found. • Image pairs starting before summer should be used to derive yearly ice velocities. • Velocity trends should be done for each pixel to properly display ice behavior. [ABSTRACT FROM AUTHOR]

Currently widespread in new urban projects, green roofs have shown a positive impact on urban runoff at the building scale: decrease and slow-down of the peak discharge, and decrease of runoff volume. The present work aims to study their possible impact at the catchment scale, more compatible with stormwater management issues. For this purpose, a specific module dedicated to simulating the hydrological behaviour of a green roof has been developed in the distributed rainfall-runoff model (Multi-Hydro). It has been applied on a French urban catchment where most of the building roofs are flat and assumed to accept the implementation of a green roof. Catchment responses to several rainfall events covering a wide range of meteorological situations have been simulated. The simulation results show green roofs can significantly reduce runoff volume and the magnitude of peak discharge (up to 80%) depending on the rainfall event and initial saturation of the substrate. Additional tests have been made to assess the susceptibility of this response regarding both spatial distributions of green roofs and precipitation. It appears that the total area of greened roofs is more important than their locations. On the other hand, peak discharge reduction seems to be clearly dependent on spatial distribution of precipitation. [ABSTRACT FROM AUTHOR]

The Lower Middle Zambezi Basin is sandwiched between three hydropower dams; Kariba, Kafue (Itezhi-tezhi) and Cahora Bassa. The operation of the upstream dams impacts on the inflows into the downstream Cahora Bassa Dam which, in turn, affects the area inundated upstream of the Cahora Bassa Dam. This study applied a rainfall-runoff model (HEC-HMS) and GIS techniques to estimate both the gauged and ungauged runoff contribution to the water balance of Cahora Bassa. The rivers considered in the study are the Zambezi, Kafue, Luangwa, Chongwe, Musengezi and Manyame. Missing data were generated using the mean value infilling method. The DEM hydro-processing technique was used to determine the spatial extent of the ungauged area. A hydrological model, HEC- HMS, was used to simulate runoff from the ungauged catchments. Results from the study show that the ungauged catchment contributes about 12% of the total estimated inflows into the Cahora Bassa Dam. Averaged results over 30 years show total inflows of 71.73 x 109 m³/yr, total outflows of 52.25 x 109 m³/ yr and a residual storage of 20 x 109 m³/yr. The study successfully estimated the water balance of the Middle Zambezi Basin which, in turn, may help to inform the operation of the Cahora Bassa Dam and management of artificial floods in the basin. [ABSTRACT FROM AUTHOR]

Runoff and sediment flow behaviors from small agricultural watersheds on Alfisols and Vertic Inceptisols, and their implications for the design of a runoff and soil loss monitoring unit are discussed. It was observed that a small segment of runoff hydrograph near peak discharge rate usually accounted for 65–85 percent of total storm soil loss. The runoff and sediment flow behavior recorded on the small agricultural watersheds indicated the need for an integrated digital runoff and soil loss monitoring unit (IDRSMU) to achieve higher accuracy and cost effectiveness. The design, development and testing of an IDRSMU to measure both the runoff and soil loss from small agricultural watersheds is presented. Under the field conditions its accuracy and efficiency for monitoring soil loss from small agricultural watersheds was observed good. Use of this integrated unit, makes the estimation of soil loss easy, rapid and accurate. The designed unit does smart runoff sampling by linking the runoff sampling intervals to the sediment load. This significantly reduces number of samples that needs to be collected, thereby reducing the operational cost, without compromising with the accuracy in estimating soil loss from small agricultural watersheds. [ABSTRACT FROM AUTHOR]

Sensitivity analysis of a model can identify key variables affecting the performance of the model. Uncertainty analysis is an essential indicator of the precision of the model. In this study, the sensitivity and uncertainty of the Long-Term Hydrologic Impact Assessment-Low Impact Development 2.1 (L-THIA-LID 2.1) model in estimating runoff and water quality were analyzed in an urbanized watershed in central Indiana, USA, using Sobol′'s global sensitivity analysis method and the bootstrap method, respectively. When estimating runoff volume and pollutant loads for the case in which no best management practices (BMPs) and no low impact development (LID) practices were implemented, CN (Curve Number) was the most sensitive variable and the most important variable when calibrating the model before implementing practices. When predicting water quantity and quality with varying levels of BMPs and LID practices implemented, Ratio_r (Practice outflow runoff volume/inflow runoff volume) was the most sensitive variable and therefore the most important variable to calibrate the model with practices implemented. The output uncertainty bounds before implementing BMPs and LID practices were relatively large, while the uncertainty ranges of model outputs with practices implemented were relatively small. The limited observed data in the same study area and results from other urban watersheds in scientific literature were either well within or close to the uncertainty ranges determined in this study, indicating the L-THIA-LID 2.1 model has good precision. [ABSTRACT FROM AUTHOR]

Solute transport in aquifers is strongly influenced by the spatial distribution of subsurface hydraulic conductivity (K), while limited drilling typically results in lack of data characterizing both the K and the in situ fluid-flow boundary conditions (BC). To characterize such environments, this paper presents an efficient direct inverse method to simultaneously identify an aquifer's K pattern, values, and flow field. The method ensures fluid-flow continuity using local approximate solutions of the governing flow equation conditioned to limited measurements, while the physics of flow are enforced, making the inverse problem well-posed. A single system of equations is assembled and solved, from which parameters and BC can be simultaneously estimated. For problems with irregular and regular K distributions, inversion is demonstrated for different measurement types, qualities, and quantities. When measurement error is increased, the estimated K pattern is largely insensitive to the error, although the inverted flow field suffers greater inaccuracy. Local conductivity and Darcy flux measurements are found to have similar information content, although subtle differences exist in the inversion outcomes when long-term contaminant release is simulated. Local conductivity measurements lead to better identification of conductivity pattern, values, and hydraulic head field; Darcy flux measurements lead to more-accurate estimation of the velocity field and thus improved transport predictions. Overall, velocity field estimated by the direct inverse method based on hydraulic measurements can lead to reasonable predictions of contaminant migration under unknown aquifer BC. [ABSTRACT FROM AUTHOR]

Regions with long-term animal manure applications based on nitrogen (N) requirements have concerns regarding elevated nutrient levels. Most attention has focused on phosphorus (P), but heavy metal accumulation has received attention due to perceived environmental concerns. Composting is a potential management practice that can reduce total manure mass and volume while creating a stabilized product that has less odor and fewer pathogens. However, composting animal manures can lead to high N loss via ammonia volatilization and increased concentrations of nonvolatile nutrients. The objective of this study was to measure copper (Cu) and zinc (Zn) concentrations in runoff water from plots fertilized with composted and fresh poultry litter. Seven treatments were evaluated in the first year: (i) unfertilized control, (ii) fresh poultry litter, (iii) normal compost (no amendment), (iv) composted litter with alum, (v) composted litter with phosphoric acid, (vi) composted litter with a microbial mixture, and (vii) composted litter with alum + microbial mixture. Six of these treatments were evaluated in Year 2 (alum + microbial mixture was not evaluated in Year 2). Rainfall simulators were used to produce a 5 cm h-1 storm event sufficient in length to cause 30 min of continuous runoff. Concentrations of Cu and Zn were elevated in compost compared with fresh poultry litter. However, metal concentrations in compost did not correlate well with metal concentrations in runoff water and may have been affected by compost maturity and amendment. Total Cu and Zn concentrations in runoff water did not differ between alum-amended compost and fresh poultry litter in each year. [ABSTRACT FROM AUTHOR]

Effect of climate change and catchment change on the long-term water balance is of considerable interest at a range of spatial scales. The total differential of runoff within the Budyko framework, which has been widely used to attribute the change in runoff to the effect of climate and catchment changes, is not precise in which there is always some residual between the observed and estimated change in runoff. The objective of this study is to propose and evaluate a new partition method based on the Budyko complementary relationship for runoff. Algebraic identities have ensured that the change in runoff can be decomposed into two components precisely without any residuals using this complementary method. In addition, the complementary method allows estimation of the upper and lower bounds of the climate effect and catchment effect. The new method was compared with the total differential method and an extrapolation method for 15 catchments in Australia. Results show that the average range of the catchment effect using the complementary method was 6.7 mm for 14 of the 15 catchments, which is much smaller than that estimated with the total differential method (51.5 mm). The average of the upper and lower bounds was shown to be in good agreement with the effect of climate and catchment changes estimated using the extrapolation method (R2 = 0.98 for both). Correlation analysis indicates that the average of these bounds is the best estimate of the magnitude of the climate and catchment effect for the 15 catchments examined. [ABSTRACT FROM AUTHOR]

This study investigates the temporal variability of zinc concentrations from zinc roof runoff. The influence of rainfall characteristics and dry period duration is evaluated by combining laboratory experiment on small zinc sheets and in situ measurements under real weather conditions from a 1.6-m zinc panel. A reformulation of a commonly used conceptual runoff quality model is introduced and its ability to simulate the evolution of zinc concentrations is evaluated. A systematic and sharp decrease from initially high to relatively low and stable zinc concentrations after 0.5 to 2 mm of rainfall is observed for both experiments, suggesting that highly soluble corrosion products are removed at early stages of runoff. A moderate dependence between antecedent dry period duration and the magnitude of zinc concentrations at the beginning of a rain event is evidenced. Contrariwise, results indicate that concentrations are not significantly influenced by rainfall intensities. Simulated rainfall experiment nonetheless suggests that a slight effect of rainfall intensities may be expected after the initial decrease of concentrations. Finally, this study shows that relatively simple conceptual runoff quality models may be adopted to simulate the variability of zinc concentrations during a rain event and from a rain event to another. [ABSTRACT FROM AUTHOR]

Rainfall maps that are derived from satellite observations provide hydrologists with an unprecedented opportunity to forecast floods globally. However, the limitations of using these precipitation estimates with respect to producing reliable flood forecasts at multiple scales are not well understood. To address the scientific and practical question of applicability of space-based rainfall products for global flood forecasting, a data evaluation framework is developed that allows tracking the rainfall effects in space and time across scales in the river network. This provides insights on the effects of rainfall product resolution and uncertainty. Obtaining such insights is not possible when the hydrologic evaluation is based on discharge observations from single gauges. The proposed framework also explores the ability of hydrologic model structure to answer questions pertaining to the utility of space-based rainfall observations for flood forecasting. To illustrate the framework, hydrometeorological data collected during the Iowa Flood Studies (IFloodS) campaign in Iowa are used to perform a hydrologic simulation using two different rainfall-runoff model structures and three rainfall products, two of which are radar based [stage IV and Iowa Flood Center (IFC)] and one satellite based [TMPA-Research Version (RV)]. This allows for exploring the differences in rainfall estimates at several spatial and temporal scales and provides improved understanding of how these differences affect flood predictions at multiple basin scales. The framework allows for exploring the differences in peak flow estimation due to nonlinearities in the hydrologic model structure and determining how these differences behave with an increase in the upstream area through the drainage network. The framework provides an alternative evaluation of precipitation estimates, based on the diagnostics of hydrological model results. [ABSTRACT FROM AUTHOR]

In this study, a Bayesian framework is proposed for investigating uncertainties in input data (i.e., temperature and precipitation) and parameters in a distributed hydrological model as well as their effects on the runoff response in the Kaidu watershed (a snowmelt-precipitation-driven watershed). In the Bayesian framework, the Soil and Water Assessment Tool (SWAT) is used for providing the basic hydrologic protocols. The Delayed Rejection Adaptive Metropolis (DRAM) algorithm is employed for the inference of uncertainties in input data and model parameters with global and local adaptive strategies. The advanced Bayesian framework can help facilitate the exploration of variation of model parameters due to input data errors, as well as propagation from uncertainties in data and parameters to model outputs in both snow-melting and nonmelting periods. A series of calibration cases corresponding to data errors under different periods are examined. Results show that 1) input data errors can affect the distributions of model parameters as well as parameters' correlation, implying that data errors could influence the related hydrologic processes as well as their relations; 2) considering input data errors could improve the hydrologic simulation ability for peak streamflows; 3) considering errors of temperature and precipitation data as well as uncertainties of model parameters can provide the best modeling simulation performance in the snow-melting period; and 4) accounting for uncertainties in precipitation data and model parameters can provide the best modeling performance during the nonmelting period. The findings will help enhance hydrological model's capability for simulating/predicting water resources during different seasons for snowmelt-precipitation-driven watersheds. [ABSTRACT FROM AUTHOR]

We challenge the assertions of the study by Gupta et al. (doi:) that land use, land cover change (LULC) has had minimal or no effect on hydrology in Minnesota's rivers. Statistical analyses actually demonstrate that something other than changes in precipitation (and soil moisture) must be contributing to increases in runoff ratio and flow. The analysis presented by Gupta et al. (doi:) fails to directly address the fundamental purpose and mechanism of artificial drainage, which is to reduce water residence time on the landscape, thereby reducing ET (and soil wetness) and routing this water to rivers instead. [ABSTRACT FROM AUTHOR]

The empirical proportionality relationship, which indicates that the ratio of cumulative surface runoff and infiltration to their corresponding potentials are equal, is the basis of the extensively used Soil Conservation Service Curve Number (SCS-CN) method. The objective of this paper is to provide the physical basis of the SCS-CN method and its proportionality hypothesis from the infiltration excess runoff generation perspective. To achieve this purpose, an analytical solution of Richards' equation is derived for ponded infiltration in shallow water table environment under the following boundary conditions: (1) the soil is saturated at the land surface; and (2) there is a no-flux boundary which moves downward. The solution is established based on the assumptions of negligible gravitational effect, constant soil water diffusivity, and hydrostatic soil moisture profile between the no-flux boundary and water table. Based on the derived analytical solution, the proportionality hypothesis is a reasonable approximation for rainfall partitioning at the early stage of ponded infiltration in areas with a shallow water table for coarse textured soils. [ABSTRACT FROM AUTHOR]

Application of organic wastes to cultivated lands can replace mineral fertilizers but may also alter soil physical properties and enhance pollution potential. The objective of this study was to investigate the effects of biosolids [composted manure (MC) and activated sludge (AS)] and specific biosolid component [orthophosphate (OP), phytic acid (PA) and humic acid (HA)] application on soils differing in texture [loamy-sand (Ramat-HaKovesh, RH), loam (Gilat, GL) and clay (Bet-Dagan, BD)], infiltration rate, runoff volume and soil sediment loss. The soils were packed in erosion boxes (400 × 200 × 40 mm) and subjected to six consecutive simulated rainstorms, each of 186 mm deionized water. The results showed that runoff volume and sediment loss from untreated soils increased with increasing clay contents. In treated soils, the response to AS application differed from the response to other amendments; in the BD clay and GL loam, it was the only amendment that caused a decrease in sediment removed by runoff. In the RH loamy-sand, all amendments reduced the final infiltration rate, but only AS and HA increased the measured runoff. It is proposed that the difference in the response of the soils to the amendments is associated with the soil's ability to attenuate changes in the negative charge on the clay edges following the increase in the specific adsorption of charged anions, thus controlling clay swelling and maintaining aggregate integrity. The effects of amending soils with a source of organic matter in order to control runoff and soil erosion are not straight forward and depend on soil and amendment properties. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This study investigates the impact of event characteristics on runoff dynamics during extreme flood events observed in an 8.5-km² experimental watershed located in South Korea. A high-quality data set containing the 31 most extreme flood events with event rainfall in excess of 50 mm were analyzed using an event-based rainfall-runoff model; the revitalized flood hydrograph (ReFH) routinely used for design flood estimation in the United Kingdom. The ReFH model was fitted to each event in turn, and links were investigated between each of the two model parameters controlling runoff volume and response time, respectively, and event characteristics such as rainfall depth, duration, and intensity, and also antecedent soil moisture. The results show no link between the parameter controlling runoff volume and any of the event characteristics, but identified a dependence between response time and rainfall depth. These results show that the linear unit hydrograph fails to adequately represent a reduction in watershed response time observed for the more extreme events. A new and dynamic link between the unit hydrograph shape and rainfall depth is introduced. The consequence of the observed nonlinearity in response time is to increase design peak flow by between 50% for a 10-year return period, and up to 80% when considering the probable maximum flood. [ABSTRACT FROM AUTHOR]

The Tibetan Plateau (TP) plays a major role in regional and global climate. The understanding of latent heat (LE) flux can help to better describe the complex mechanisms and interactions between land and atmosphere. Despite its importance, accurate estimation of evapotranspiration (ET) over the TP remains challenging. Satellite observations allow for ET estimation at high temporal and spatial scales. The purpose of this paper is to provide a detailed cross-comparison of existing ET products over the TP. Six available ET products based on different approaches are included for comparison. Results show that all products capture the seasonal variability well with minimum ET in the winter and maximum ET in the summer. Regarding the spatial pattern, the High resOlution Land Atmosphere surface Parameters from Space (HOLAPS) ET demonstrator dataset is very similar to the LandFlux-EVAL dataset (a benchmark ET product from the Global Energy and Water Cycle Experiment), with decreasing ET from the south-east to northwest over the TP. Further comparison against the LandFlux-EVAL over different sub-regions that are decided by different intervals of normalised difference vegetation index (NDVI), precipitation, and elevation reveals that HOLAPS agrees best with LandFlux-EVAL having the highest correlation coefficient (R) and the lowest root mean square difference (RMSD). These results indicate the potential for the application of the HOLAPS demonstrator dataset in understanding the land--atmosphere--biosphere interactions over the TP. In order to provide more accurate ET over the TP, model calibration, high accuracy forcing dataset, appropriate in situ measurements as well as other hydrological data such as runoff measurements are still needed. [ABSTRACT FROM AUTHOR]

The problem of runoff prediction taking into account the possible climate change is considered using the Bayesian approach. The proposed technique is applied to the probabilistic forecasting of minimum runoff variations on the rivers of the Volga River basin. [ABSTRACT FROM AUTHOR]

River runoff is an essential climate variable as it is directly linked to the terrestrial water balance and controls a wide range of climatological and ecological processes. Despite its scientific and societal importance, there are to date no pan-European observation-based runoff estimates available. Here we employ a recently developed methodology to estimate monthly runoff rates on regular spatial grid in Europe. For this we first assemble an unprecedented collection of river flow observations, combining information from three distinct databases. Observed monthly runoff rates are subsequently tested for homogeneity and then related to gridded atmospheric variables (E-OBS version 12) using machine learning. The resulting statistical model is then used to estimate monthly runoff rates (December 1950-December 2015) on a 0°.5x0.5° grid. The performance of the newly derived runoff estimates is assessed in terms of cross validation. The paper closes with example applications, illustrating the potential of the new runoff estimates for climatological assessments and drought monitoring. [ABSTRACT FROM AUTHOR]

As urbanization increases, urban runoff becomes an increasingly more important component of urban non-point pollution. In this study, the Storm Water Management Model was used to simulate the quantity and quality of runoff in a highly urbanized catchment. Data from three rainfall events were collected and used for model calibration and validation. Model performance was assessed using the Nash-Sutcliffe coefficient, relative error, and coefficient of determination. The modified Morris screening method was used for local sensitivity analysis. Sensitivity analysis results showed that the destore imperv and condit roughness parameters had the most influence on the hydrology and hydraulic module. Road exponent was the most sensitive parameter in determining TSS quantity and peak concentration. The calibration and verification results indicated that the model structure and parameters fitted the runoff-producing pattern. The total simulation accuracies of TSS, TN, TP, and COD loads, as assessed by the R2 value, were 0.82, 0.87, 0.72, and 0.94, respectively. [ABSTRACT FROM AUTHOR]

Metals such as antimony, cadmium, chromium, copper, lead, nickel, and zinc can be highly relevant pollutants in stormwater runoff from traffic areas because of their occurrence, toxicity, and non-degradability. Long-term measurements of their concentrations, the corresponding water volumes, the catchment areas, and the traffic volumes can be used to calculate specific emission loads and annual runoff loads that are necessary for mass balances. In the literature, the annual runoff loads are often specified by a distinct catchment area (e.g., g/ha). These loads were summarized and discussed in this paper for all seven metals and three types of traffic areas (highways, parking lots, and roads; 45 sites). For example, the calculated median annual runoff loads of all sites are 355 g/ha for copper, 110 g/ha for lead (only data of the 21st century), and 1960 g/ha for zinc. In addition, historical trends, annual variations, and site-specific factors were evaluated for the runoff loads. For Germany, mass balances of traffic related emissions and annual heavy metal runoff loads from highways and total traffic areas were calculated. The influences on the mass fluxes of the heavy metal emissions and the runoff pollution were discussed. However, a statistical analysis of the annual traffic related metal fluxes, in particular for different traffic area categories and land uses, is currently not possible because of a lack of monitoring data. [ABSTRACT FROM AUTHOR]

The Long Term Hydrologic Impact Assessment (L-THIA) model was previously improved by incorporating direct runoff lag time and baseflow. However, the improved model, called the L-THIA asymptotic curve number (ACN) model cannot simulate pollutant loads from a watershed or instream water quality. In this study, a module for calculating pollutant loads from fields and through stream networks was developed, and the L-THIA ACN model was combined with the QUAL2E model (The enhanced stream water quality model) to predict instream water quality at a watershed scale. The new model (L-THIA ACN-WQ) was applied to two watersheds within the Korean total maximum daily loads management system. To evaluate the model, simulated results of total nitrogen (TN) and total phosphorus (TP) were compared with observed water quality data collected at eight-day intervals. Between simulated and observed data for TN pollutant loads in Dalcheon A watershed, the R2 and Nash-Sutcliffe efficiency (NSE) were 0.81 and 0.79, respectively, and those for TP were 0.79 and 0.78, respectively. In the Pyungchang A watershed, the R2 and NSE were 0.66 and 0.64, respectively, for TN and both statistics were 0.66 for TP, indicating that model performed satisfactorily for both watersheds. Thus, the L-THIA ACN-WQ model can accurately simulate streamflow, instream pollutant loads, and water quality. [ABSTRACT FROM AUTHOR]

Understanding runoff generation and dynamics is the basis for water resource management, while water isotopic ratios are a potential tool for studying the mechanism on a large scale. In this paper, spatial variations of δ18O and δD of river water and their sources within a large region of the Tarim River were investigated. The results showed obvious spatial variations of both water isotope values along the river flow direction, and significant seasonal variation occurred within the river water isotopes. This indicated that different proportions of rain and melt water entering river water should lead to spatial variation, and for mid-stream and downstream regions, the transformation relationship between surface water and groundwater should consider less input of melt water. Furthermore, we quantitatively determine the ratio of different water sources using the stable isotope mass balance method and other stable tracer elements. Results showed the contribution of ice-snowmelt water varied from 14.97% to 40.85%, that of rain varied from 9.04% to 54.80%, and that of groundwater varied from 15.34% to 58.85%, and they also showed that baseflow is a factor connecting melt water and groundwater, which meant the Hotan River and the Yarkand River are melt water-dependent rivers, and seasonal precipitation is the main water supply source of baseflow in the Aksu River and the Kaidu River. [ABSTRACT FROM AUTHOR]

Winter road network management is a source of anthropogenic salinity in the Saint-Augustin Lake watershed (Quebec City, QC, Canada). To prevent the potential impact caused by road runoff involving de-icing salts (NaCl) and trace metals (Cd and Pb) on the watershed, a full-scale treatment chain system (including a detention basin, a filtering bed, and a constructed wetland) was built. Average Cl and Na concentrations in groundwater were higher in wells affected by road network (125 mg/L Cl and 64 mg/L Na) than in control wells (13 mg/L Cl and 33 mg/L Na) suggesting a contamination by de-icing salts. The monitoring of influent and effluent surface water in the treatment system has shown a seasonal dependence in NaCl concentrations and electrical conductivity values, being the highest in summer, linked with the lower precipitation and higher temperature. Concentration ranges were as follows: 114-846 mg/L Na and 158-1757 mg/L Cl (summer) > 61-559 mg/L Na and 63-799 mg/L Cl (spring and autumn). The treatment system removal efficiency was significant, however with seasonal variations: 16%-20% Cl, 3%-25% Na, 7%-10% Cd and 7%-36% Pb. The treatment system has shown an interesting potential to mitigate the impact of anthropogenic salinity at watershed scale with higher expected performances in the subsequent years of operation. [ABSTRACT FROM AUTHOR]

Artificial neural networks (ANN) are applicable for and forecasting without the need to calculate complex nonlinear functions. This paper evaluates the effectiveness of temperature, evapotranspiration, precipitation and inflow factors, and the lag time of those factors, as variables for simulating and forecasting of runoff. The genetic algorithm (GA) is coupled with ANN to determine the optimal set of variables for streamflow forecasting. The minimization of the total mean square error (MSE) is considered as the objective function of the ANN-GA method in this paper. Our results show the effectiveness of the ANN-GA for simulating and forecasting runoff with consistent accuracy compared with using pure ANN for runoff simulation and forecasting. [ABSTRACT FROM AUTHOR]

A parameter regionalization scheme to transfer parameter values from gaged to ungaged areas for a monthly water balance model (MWBM) was developed and tested for the conterminous United States (CONUS). The Fourier Amplitude Sensitivity Test, a global-sensitivity algorithm, was implemented on a MWBM to generate parameter sensitivities on a set of 109 951 hydrologic response units (HRUs) across the CONUS. The HRUs were grouped into 110 calibration regions based on similar parameter sensitivities. Subsequently, measured runoff from 1575 streamgages within the calibration regions were used to calibrate the MWBM parameters to produce parameter sets for each calibration region. Measured and simulated runoff at the 1575 streamgages showed good correspondence for the majority of the CONUS, with a median computed Nash-Sutcliffe efficiency coefficient of 0.76 over all streamgages. These methods maximize the use of available runoff information, resulting in a calibrated CONUS-wide application of the MWBM suitable for providing estimates of water availability at the HRU resolution for both gaged and ungaged areas of the CONUS. [ABSTRACT FROM AUTHOR]

Green (vegetated) roofs provide many beneficial environmental services but can also pose a disservice by leaching nutrients and metals, via storm water runoff, to downstream aquatic ecosystems. Current estimates of water quality impacts rely on limited samples (snapshots in time) and may not accurately reflect the true influence of green roof ecosystems, which likely vary temporally as do natural ecosystems. Using a 46 m 2 green roof in Cincinnati, OH, we analyzed runoff from >80 events over two years for pH, conductivity, and concentrations of dissolved nutrients, base cations, and metals. We related the variation in water chemistry to environmental variables including air temperature, storm event magnitude, and estimated antecedent moisture. We observed strong seasonal patterns in bioactive elements, with carbon, nitrogen, phosphorus, and base cation concentrations highest in the summer, and positively correlated with temperature. This suggests temperature-mediated processes such as microbial mineralization of organic matter, desorption or weathering, rather than plant uptake or hydrologic variation among storms, are the major controlling mechanisms for runoff water quality in this newly constructed green roof. The large temporal variation in green roof effluent water quality supports the need for long-term studies to characterize the complexity of these engineered ecosystems and their responsiveness to environmental variation. [ABSTRACT FROM AUTHOR]

The aim of this paper is to propose a new geomorphologic method for deriving the complete shape of instantaneous unit hydrograph (IUH) in ungauged watersheds by calculating the mean travel time of excess rainfall in overland and channel segments. All required parameters for the calculations of travel time of sheet and channel flows for different hydrologic orders are determined based on geomorphologic data of a watershed. In the proposed model, IUH is obtained using the exponential probability density function (PDF) of mean travel time of possible flow paths in a watershed. In this method, the excess rainfall is determined using the National Resources Conservation Service) NRCS curve number (CN) method (SCS-CN). To investigate the performance of the proposed IUH model, it is applied for daily rainfall-runoff simulation in two separate watersheds with different climate conditions (i.e., cool-humid and semiarid) in Iran. Also, other geomorphologic IUH (GIUH) models are utilized as benchmark models for comparing their results with those obtained using the proposed model. The goodness-of-fit criteria show that the proposed GIUH model practically provides direct runoff ordinates in ungauged and partially geomorphologically homogeneous watersheds with an accuracy slightly better than one of the other GIUH (especially in terms of estimating peak flow) and much better than the other GIUH model. Additionally, the proposed model is beneficial to estimate the travel time of overland and channel flows in different orders of watershed, which can be worthwhile for flood management and designing flood warning systems in each segment of the watershed. [ABSTRACT FROM AUTHOR]

Climate change is likely to have significant effects on the water cycle in glacierized basins. Here, the glacier-enhanced Soil and Water Assessment Tool (SWAT) was employed to simulate glacio-hydrological processes and to estimate the potential hydrological changes driven by downscaled future climate projections of five Global Circulation Models (GCMs) under three Representative Concentration Pathways (RCPs) in the headwaters of the Urumqi River, Tianshan Mountains, China. The evaluation indices indicated that the model performed well at simulating streamflow during the calibration and validation. The GCM-predicted mean temperature and precipitation both increase. The periods of 1966-1995, 2016-2045 and 2066-2095 were used as the baseline, the near future, and the far future periods, respectively. The results showed different runoff characteristics under various scenarios in the Urumqi Glacier No. 1 (UG1) sub-basin and Urumqi River Basin (URB) due to distinct melt water contributions. In the UG1 sub-basin, the ice melt and glacier melt are expected to reach peak water in the near future and sharply decline in the far future, and the sub-basin runoff would gradually decrease under all RCPs. In the URB, the ice melt and glacier melt rapidly decrease but the river runoff remains stable under RCP 2.6 and RCP 4.5, with a slight decrease under RCP 8.5. The grouped glacier area with small size class shows a rapid retreat rate. It was also found that melt water from three grouped glaciers exhibit different responses to future scenarios. [ABSTRACT FROM AUTHOR]

A distributed physically based model, soil and water assessment tool (SWAT), and a distributed conceptual model, distributed large basin runoff model (DLBRM), were selected to compare their applicability and performance in simulating daily runoff in the Heihe River watershed, the second-largest inland river (terminal lake) with a peak elevation of 5,584 m above sea level (asl) in arid northwest China. Both models have been calibrated against the observed daily runoff at the watershed outlet (Yingluoxia Hydrological Station) for the period of 1995-2004 and validated for the period of 2005-2009. Results show that both SWAT and DLBRM produced reasonable results in this study, and DLBRM performed better than SWAT. The difference in performance is mainly due to data constraints, different interpolation schemes, and spatial representations of landscape variations in the models. The tank storage-output principle used in DLBRM seems more suitable than the Soil Conservation Service curve number (SCS-CN) method used in SWAT to simulate daily flow in an arid area. Both models performed worse in simulating low flows mostly occurring in spring and winter, because of a lack of detailed representation of the impacts of snow-melting processes and frozen soils. The authors' analysis indicates that consideration of the impacts of snow melting and frozen soils on the hydrological process is key to improving performance of hydrological models in mountainous areas. Because of their simpler operations, lower data requirements, fewer input parameters, and better performances, distributed conceptual models such as DLBRM seem more suitable for hydrological modeling in data-deficient, high elevation, and topographically complex mountainous watersheds in arid regions. [ABSTRACT FROM AUTHOR]

This study presents a remote sensing and geographic information systems-based approach for using US EPA’s Storm Water Management Model (SWMM) in urban environment. Cartosat-1 PAN + IRS-P6 LISS-IV merged product was used to map land cover in part of Surat city at 1:10,000 scale. Cartosat-1 stereo pair was used for deriving digital elevation model of the study area. Geo-informatics-based methods were developed for delineation of sub-catchment areas, assignment of sub-catchment outlets and estimation of characteristic width. It was observed that 59% of the developed area in the study region was directly or indirectly connected to the storm water drainage network. Furthermore, dynamic rainfall-runoff simulation on three-day rainfall indicated that the average runoff coefficient on the urbanized sub-catchment areas which were directly connected to the drainage network was 0.92 as against 0.88 on those urbanized sub-catchments without having direct access to storm water drainage. [ABSTRACT FROM PUBLISHER]

In mountainous watersheds, rainfall generates runoff quickly because of the decreased depression storage, high downslope flow velocity, and smaller chance for rainwater infiltration. In order to obtain precise event-based runoff estimations in mountainous watersheds, a slope-adjusted curve number (CNIIα) with a smaller initial abstraction ratio (λ) is indispensable in the standard natural resources conservation service (NRCS) curve number (CN) model. Using measured rainfall-runoff data from 39 mountainous watersheds in South Korea, this study investigated two existing CNIIα approaches and suggested a new approach that was accompanied by a lower λ value. The new CNIIα equation was calibrated with 1,402 measured rainfall-runoff events from 31 watersheds and validated with 377 rainfall-runoff events from the remaining eight watersheds. Most of the runoff events, used for both calibration and validation, were underestimated using a CN without a slope-adjusting factor. By considering the combined effect of the proposed CNIIα and setting λ equal to 0.01, the performance measures based on the root mean squares error (in mm), Nash-Sutcliffe efficiency, and coefficient of determination were significantly improved from averages of 27.10, 0.64, and 0.75 to 18.69, 0.82, and 0.87, respectively, as compared to the standard NRCS model. The proposed modification exhibited superior results compared to the two existing CNIIα approaches. Findings from this study support the adjustment of both the CN and λ in the NRCS model to increase its runoff prediction capabilities. [ABSTRACT FROM AUTHOR]

Landscaping paradigms that encourage high-input, intensively managed and mono-culture turf/lawn landscapes have raised concerns about water quality. We conducted a watershed-scale assessment of landscaping practices that included turf, urban, forest, native meadow, and mixed landuse watersheds with a professional golf course and a parking lot. The turf site was moderately managed and had lower fertilizer inputs than those typically used by homeowners and golf courses. Stream water sampling was performed during base flow and storm events. Highest nitrate and total nitrogen concentrations in runoff were observed for the mixed watershed draining the golf course. In contrast, concentrations in base flow from the turf watershed were lower than expected and were comparable to those measured in the surrounding meadow and forest sites. Total nitrogen concentrations from the turf site increased sharply during the first storms following fertilization, suggesting that despite optimal management there exists a risk for nutrient runoff following fertilization. Overall, this study suggests that turf or lawns, when managed properly, pose minimal water quality risk to surface waters. Rate, timing of application, and the type of fertilizer appear to be the key factors affecting water quality. Better education of homeowners and landscaping professionals with regard to these factors may be a cost-effective strategy to reduce nonpoint source pollution. [ABSTRACT FROM AUTHOR]