Relevant bibliographies by topics / Rainfall-runoff

Academic literature on the topic 'Rainfall-runoff'

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Published: 4 June 2021
Last updated: 10 March 2023

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Journal articles on the topic "Rainfall-runoff"

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Bartlett, M. S., E. Daly, J. J. McDonnell, A. J. Parolari, and A. Porporato. "Stochastic rainfall-runoff model with explicit soil moisture dynamics." Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences 471, no. 2183 (November 2015): 20150389. http://dx.doi.org/10.1098/rspa.2015.0389.

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Stream runoff is perhaps the most poorly represented process in ecohydrological stochastic soil moisture models. Here we present a rainfall-runoff model with a new stochastic description of runoff linked to soil moisture dynamics. We describe the rainfall-runoff system as the joint probability density function (PDF) of rainfall, soil moisture and runoff forced by random, instantaneous jumps of rainfall. We develop a master equation for the soil moisture PDF that accounts explicitly for a general state-dependent rainfall-runoff transformation. This framework is then used to derive the joint rainfall-runoff and soil moisture-runoff PDFs. Runoff is initiated by a soil moisture threshold and a linear progressive partitioning of rainfall based on the soil moisture status. We explore the dependence of the PDFs on the rainfall occurrence PDF (homogeneous or state-dependent Poisson process) and the rainfall magnitude PDF (exponential or mixed-exponential distribution). We calibrate the model to 63 years of rainfall and runoff data from the Upper Little Tennessee watershed (USA) and show how the new model can reproduce the measured runoff PDF.
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Zhou, Ke. "A comparative study on rainfall runoff control indicators of green roof." Water Supply 20, no. 6 (May 4, 2020): 2036–42. http://dx.doi.org/10.2166/ws.2020.076.

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Abstract The rainfall runoff reduction effect on green roofs was analyzed and tested by comparative rainfall runoff monitoring on impermeable roofs (sloping, plane). The evaluation index of rainfall runoff interception benefit (relative runoff reduction rate, rainfall control rate) on green roofs was studied. The results show that compared with sloping and level roofs, the change range of green roof runoff reduction rate relative to level and sloping roofs is 20.0–98.3% and 3.8–92.3%, and the mean value is 48.4% and 34.3% respectively. It is obvious that the green roof has better rainfall runoff reduction effect. It can be seen from the single rainfall control effect that the variation range of green roof rainfall runoff control rate is 36.0% to 99.0%, and the total rainfall control rate is 57.6%, which reflects that the green roof has the better rainfall control effect. Through comparative study, it can be concluded that the rainfall runoff control rate is more suitable for the design index of green roofs.
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Buchtele, Josef. "Runoff changes simulated using a rainfall-runoff model." Water Resources Management 7, no. 4 (1993): 273–87. http://dx.doi.org/10.1007/bf00872285.

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Máca, P., and P. Torfs. "The influence of temporal rainfall distribution in the flood runoff modelling." Soil and Water Research 4, Special Issue 2 (March 19, 2010): S102—S110. http://dx.doi.org/10.17221/471-swr.

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The rainfall input is one of the main factors influencing the magnitude of the runoff response during a flood event. Its temporal and spatial distribution significantly contributes to the formation of hydrograph shape, peak discharge and flood volume. A novel approach to the evaluation of the role of the temporal rainfall pattern of hydrograph is presented in this contribution. The methodology shown is based on the coupling of the deterministic event based runoff model with the stochastic rainfall disaggregation model. The rainfall model simulates the hyetograph ensemble, which is the direct input to the calibrated event based runoff model. The event based runoff model calibration is based on the evaluation of real flood events. The rainfall ensemble is simulated according to the preservation of important statistical properties, which are estimated from the real rainfall data inputs. The proposed combination of two simulation techniques enables to generate the hydrograph ensemble upon a single flood event. The evaluation of the temporal rainfall distribution impact on the flood runoff response is performed through the determination of the selected rainfall runoff characteristics of the simulated hydrograph ensemble. The main result confirms the importance of the rainfall volume inputs and its temporal distribution on the flood runoff generation. The methodology shown enables to evaluate the potential of the real flood event to generate the flood event within the conditions of the small catchment scale.
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Herrnegger, M., H. P. Nachtnebel, and K. Schulz. "From runoff to rainfall: inverse rainfall–runoff modelling in a high temporal resolution." Hydrology and Earth System Sciences 19, no. 11 (November 23, 2015): 4619–39. http://dx.doi.org/10.5194/hess-19-4619-2015.

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Abstract. Rainfall exhibits a large spatio-temporal variability, especially in complex alpine terrain. Additionally, the density of the monitoring network in mountainous regions is low and measurements are subjected to major errors, which lead to significant uncertainties in areal rainfall estimates. In contrast, the most reliable hydrological information available refers to runoff, which in the presented work is used as input for an inverted HBV-type rainfall–runoff model that is embedded in a root finding algorithm. For every time step a rainfall value is determined, which results in a simulated runoff value closely matching the observed runoff. The inverse model is applied and tested to the Schliefau and Krems catchments, situated in the northern Austrian Alpine foothills. The correlations between inferred rainfall and station observations in the proximity of the catchments are of similar magnitude compared to the correlations between station observations and independent INCA (Integrated Nowcasting through Comprehensive Analysis) rainfall analyses provided by the Austrian Central Institute for Meteorology and Geodynamics (ZAMG). The cumulative precipitation sums also show similar dynamics. The application of the inverse model is a promising approach to obtain additional information on mean areal rainfall. This additional information is not solely limited to the simulated hourly data but also includes the aggregated daily rainfall rates, which show a significantly higher correlation to the observed values. Potential applications of the inverse model include gaining additional information on catchment rainfall for interpolation purposes, flood forecasting or the estimation of snowmelt contribution. The application is limited to (smaller) catchments, which can be represented with a lumped model setup, and to the estimation of liquid rainfall.
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Herrnegger, M., H. P. Nachtnebel, and K. Schulz. "From runoff to rainfall: inverse rainfall–runoff modelling in a high temporal resolution." Hydrology and Earth System Sciences Discussions 11, no. 12 (December 5, 2014): 13259–309. http://dx.doi.org/10.5194/hessd-11-13259-2014.

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Abstract. This paper presents a novel technique to calculate mean areal rainfall in a high temporal resolution of 60 min on the basis of an inverse conceptual rainfall–runoff model and runoff observations. Rainfall exhibits a large spatio-temporal variability, especially in complex alpine terrain. Additionally, the density of the monitoring network in mountainous regions is low and measurements are subjected to major errors, which lead to significant uncertainties in areal rainfall estimates. The most reliable hydrological information available refers to runoff, which in the presented work is used as input for a rainfall–runoff model. Thereby a conceptual, HBV-type model is embedded in an iteration algorithm. For every time step a rainfall value is determined, which results in a simulated runoff value that corresponds to the observation. To verify the existence, uniqueness and stability of the inverse rainfall, numerical experiments with synthetic hydrographs as inputs into the inverse model are carried out successfully. The application of the inverse model with runoff observations as driving input is performed for the Krems catchment (38.4 km2), situated in the northern Austrian Alpine foothills. Compared to station observations in the proximity of the catchment, the inverse rainfall sums and time series have a similar goodness of fit, as the independent INCA rainfall analysis of Austrian Central Institute for Meteorology and Geodynamics (ZAMG). Compared to observations, the inverse rainfall estimates show larger rainfall intensities. Numerical experiments show, that cold state conditions in the inverse model do not influence the inverse rainfall estimates, when considering an adequate spin-up time. The application of the inverse model is a feasible approach to obtain improved estimates of mean areal rainfall. These can be used to enhance interpolated rainfall fields, e.g. for the estimation of rainfall correction factors, the parameterisation of elevation dependency or the application in real-time flood forecasting systems.
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ADHIKARI, RN, S. CHATTARAJAN, US PATTNAIK, and MM SRJVASTAVA. "Rainfall-runoff relationship based on the model of runoff formation at the natural storage." MAUSAM 40, no. 3 (April 28, 2022): 81–84. http://dx.doi.org/10.54302/mausam.v40i3.2132.

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An attempt is mad~ to establish a relationship between rainfall and runoff. The basic input data are (i) rainfall, (ii) run off and (iii) evapotranspiration. The moisture content prior to rainfall under consideration and after the termination of rainfall is computed by water balance technique this method is applied in small agricultural catchments in Soil Conservation Research Farm at Ballary, Karnataka, which is categorised its semiarid zone of black soil region. The relationship between rainfall and runoff under different initial moisture content and rainfall intensities are found out. Attempts are also made to get relationship between moisture condition of the catchment after the end of rainfall and runoff with rainfall intensities as an additional factor. The estimated runoff obtained from various equations are compared with the observed runoff. The rainfall-runoff relationship with initial moisture content as third parameter gives encouraging results for estimation of runoff.
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Ma, Ying, He Hai Xie, and Chun Li. "Experimental Analysis on Runoff and Sediment from Sloping Lands in Karst Region." Advanced Materials Research 1073-1076 (December 2014): 1624–29. http://dx.doi.org/10.4028/www.scientific.net/amr.1073-1076.1624.

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In order to study the features of Mountainous watershed runoff and erosion in karst region, , on the basis of design of experiment of the the big pore, slope runoff and erosion, artificial rainfall runoff experiment is made, by establishing artificial rainfall, slope runoff test plot. Large quantities of data were obtained through the artificial rainfall test. According to the experimental data, under different rainfall intensity, rainfall, under the pad surface and rainfall process, regularity of slope runoff and sediment yield in karst area is studied to provide data validation for the development of slope runoff and sediment yield model in karst region.
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Liang, Rui, Qiao Zhu, Huan Lian Ren, and Hua Jin. "Analysis on Characteristics of the Rainfall-Runoff in Beizhangdian Watershed." Applied Mechanics and Materials 90-93 (September 2011): 2578–82. http://dx.doi.org/10.4028/www.scientific.net/amm.90-93.2578.

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Beizhangdian watershed is a typical semi-dry and semi-humid region, where human activities have little effect on the hydrological cycle. Based on a 30-year hydrological observation data, the precipitation, runoff, and rainfall-runoff relationship were researched by the hydrology statistics analysis methods. The results indicated that the inter-annual change of rainfall-runoff of the watershed is remarkable, the annual distribution of rainfall-runoff is extremely uneven, and rainfall-runoff mainly occurred in flood season (June ~ September). There is a good uniformity between the variation tendency of annual rainfall and annual runoff in time and amount, the correlation coefficient of rainfall and runoff is 0.74, the value of the F-test is 4.23.
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Lee, Kang, Joo, Kim, Kim, and Lee. "Hydrological Modeling Approach Using Radar-Rainfall Ensemble and Multi-Runoff-Model Blending Technique." Water 11, no. 4 (April 23, 2019): 850. http://dx.doi.org/10.3390/w11040850.

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The purpose of this study is to reduce the uncertainty in the generation of rainfall data and runoff simulations. We propose a blending technique using a rainfall ensemble and runoff simulation. To create rainfall ensembles, the probabilistic perturbation method was added to the deterministic raw radar rainfall data. Then, we used three rainfall-runoff models that use rainfall ensembles as input data to perform a runoff analysis: The tank model, storage function model, and streamflow synthesis and reservoir regulation model. The generated rainfall ensembles have increased uncertainty when the radar is underestimated, due to rainfall intensity and topographical effects. To confirm the uncertainty, 100 ensembles were created. The mean error between radar rainfall and ground rainfall was approximately 1.808–3.354 dBR. We derived a runoff hydrograph with greatly reduced uncertainty by applying the blending technique to the runoff simulation results and found that uncertainty is improved by more than 10%. The applicability of the method was confirmed by solving the problem of uncertainty in the use of rainfall radar data and runoff models.
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Dissertations / Theses on the topic "Rainfall-runoff"

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Riverso, Carlo. "Calibration of rainfall-runoff models." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2011. http://amslaurea.unibo.it/2619/.

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Abushandi, Eyad. "Rainfall-runoff modeling in arid areas." Doctoral thesis, Technische Universitaet Bergakademie Freiberg Universitaetsbibliothek "Georgius Agricola", 2011. http://nbn-resolving.de/urn:nbn:de:bsz:105-qucosa-68530.

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The Wadi Dhuliel catchment/ North east Jordan, as any other arid area has distinctive hydrological features with limited water resources. The hydrological regime is characterized by high variability of temporal and spatial rainfall distributions, flash floods, absence of base flow, and high rates of evapotranspiration. The aim of this Ph.D. thesis was to apply lumped and distributed models to simulate stream flow in the Wadi Dhuliel arid catchment. Intensive research was done to estimate the spatial and temporal rainfall distributions using remote sensing. Because most rainfall-runoff models were undertaken for other climatic zones, an attempt was made to study limitations and challenges and improve rainfall-runoff modeling in arid areas in general and for the Wadi Dhuliel in particular. The thesis is divided into three hierarchically ordered research topics. In the first part and research paper, the metric conceptual IHACRES model was applied to daily and storm events time scales, including data from 19 runoff events during the period 1986-1992. The IHACRES model was extended for snowfall in order to cope with such extreme events. The performance of the IHACRES model on daily data was rather poor while the performance on the storm events scale shows a good agreement between observed and simulated streamflow. The modeled outputs were expected to be sensitive when the observed flood was relatively small. The optimum parameter values were influenced by the length of a time series used for calibration and event specific changes. In the second research paper, the Global Satellite Mapping of Precipitation (GSMaP_MVK+) dataset was used to evaluate the precipitation rates over the Wadi Dhuliel arid catchment for the period from January 2003 to March 2008. Due to the scarcity of the ground rain gauge network, the detailed structure of the rainfall distribution was inadequate, so an independent from interpolation techniques was used. Three meteorological stations and six rain gauges were used to adjust and compare with GSMaP_MVK+ estimates. Comparisons between GSMaP_MVK+ measurements and ground rain gauge records show distinct regions of correlation, as well as areas where GSMaP_MVK+ systematically over- and underestimated ground rain gauge records. A multiple linear regression (MLR) model was used to derive the relationship between rainfall and GSMaP_MVK+ in conjunction with temperature, relative humidity, and wind speed. The MLR equations were defined for the three meteorological stations. The ‘best’ fit of the MLR model for each station was chosen and used to interpolate a multiscale temporal and spatial distribution. Results show that the rainfall distribution over the Wadi Dhuliel is characterized by clear west-east and north-south gradients. Estimates from the monthly MLR model were more reliable than estimates obtained using daily data. The adjusted GSMaP_MVK+ dataset performed well in capturing the spatial patterns of the rainfall at monthly and annual time scales, while daily estimation showed some weakness for light and moderate storms. In the third research paper, the HEC-HMS and IHACRES rainfall runoff models were applied to simulate a single streamflow event in the Wadi Dhuliel catchment that occurred in 30-31.01.2008. Both models are considered suitable for arid conditions. The HEC-HMS model application was done in conjunction with the HEC-GeoHMS extension in ArcView 3.3. Streamflow estimation was performed on hourly data. The aim of this study was to develop a new framework of rainfall-runoff model applications in arid catchment by integrating a re-adjusted satellite derived rainfall dataset (GSMaP_MVK+) to determine the location of the rainfall storm. Each model has its own input data sets. HEC-HMS input data include soil type, land use/land cover map, and slope map. IHACRES input data sets include hourly rainfall and temperature. The model was calibrated and validated using observed stream flow data collected from Al-Za’atari discharge station. IHACRES shows some weaknesses, while the flow comparison between the calibrated streamflow results agrees well with the observed streamflow data of the HEC-HMS model. The Nash-Sutcliffe efficiency (Ef) for both models was 0.51, and 0.88 respectively. The application of HEC-HMS model in this study is considered to be satisfactory.
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Al-Qurashi, Aisha Mufti Al-Sayyid Hassan. "Rainfall-runoff modelling in arid areas." Thesis, Imperial College London, 2008. http://hdl.handle.net/10044/1/8860.

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Arid areas have distinctive hydrological features substantially different from those of humid areas. The high temporal and spatial distribution of the ra;infall, flash floods, absence of base flow, sparsity of plant cover, high transmission losses, high amounts of evaporation and evapotranspiration and the general climatologies are examples of such differences. The aim of this Ph.D. research is to use advanced tools of model analysis to test some of the current models that consider arid area hydrological characteristics. As most models were mainly developed for other regions, an attempt is made to study their limitations using Omani hydrological data, providing some guidelines for improved rainfall-runoff modelling in arid areas in general and Oman in particular. Two different types of models were selected for this research; KINEROS, which is an event based, semi-distributed, physically-based model that is considered suitable to be used for arid area conditions, and, which is continuous, lumped, conceptual model. Two Omani catchments were selected to test the performance of the selected models and to identify the main uncertainties arising, to provide some recommendations regarding the suitability of these models or model types and how they might be improved, to highlight any further data that is required, and how uncertainties should be handled in model applications.
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Loague, Keith M. "An assessment of rainfall-runoff modeling methodology." Thesis, University of British Columbia, 1986. http://hdl.handle.net/2429/27131.

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This study reports model performance calculations for three event-based rainfall-runoff models on both real and synthetic data sets. The models include a regression model, a unit hydrograph model and a quasi-physically based model. The real data sets are for small upland catchments from the Washita River Experimental Watershed, Oklahoma; the Mahantango Creek Experimental Watershed, Pennsylvania; and the Hubbard Brook Experimental Forest, New Hampshire. The synthetic data sets are generated with a stochastic-conceptual rainfall-runoff simulator. Model performance is assessed for a verification period that is carefully distinguished from the calibration period. Performance assessment was carried out both in forecasting mode and in prediction mode. The results on the real data sets show surprisingly poor forecasting efficiencies for all models on all data sets. The unit hydrograph model and the quasi-physically based model have little forecasting power; the regression model is marginally better. The performance of the models in prediction mode is better. The regression model and the unit hydrograph model showed acceptable predictive power, but the quasi-physically based model produced acceptable predictions on only one of the three catchments. The performance of the regression and unit hydrograph models, in both forecasting and prediction modes, for synthetic data is much better than for the real catchments. The performance of the quasi-physically based model on a synthetic data set is surprisingly poor. Supplemental data gathered from the Oklahoma catchment was used for a spatial variability analysis of steady-state infiltration rates. These data were then used to re-excite the quasi-physically based model; the new information resulted in improved model performance. The concept of space-time tradeoffs across the hydrologic data sets of competing models is introduced and tested. Results show the existence of space-time tradeoffs within model data sets but not across model data sets. It is the belief of the author that the primary barrier to successful application of physically based models in the field lies in the scale problems that are associated with the unmeasurable spatial variability of rainfall and soil hydraulic properties. The fact that simpler, less data intensive models provided as good or better predictions than a physically based model is food for thought. The model evaluation and space-time tradeoff experiments reported in this study are conceptually linked to data-worth analysis, network-design, and model-choice criteria for future studies.
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Hawkins, Richard H. "A Taxonomy of Small Watershed Rainfall-Runoff." Arizona-Nevada Academy of Science, 1990. http://hdl.handle.net/10150/296444.

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From the Proceedings of the 1990 Meetings of the Arizona Section - American Water Resources Association and the Hydrology Section - Arizona-Nevada Academy of Science - April 21, 1990, Arizona State University, Tempe, Arizona
A study of over 11,000 event rainfall and associated direct runoff events from 100 small watersheds was done, in a search for distinct patterns of runoff response and/or association with land type. The results show unexpected variety in the geometry and scale of the rainfall -runoff response. Groupings of similar response type and magnitude were made, and the associations with vegetative cover were tested. Five separate response groups were identified as follows: 1) Inactive, characterized by no recorded responses to any rainstorm in an extended period of record; 2) Complacent, characterized by a very small part of the rainfall (ca 0.1 to 3 percent) being converted to direct runoff, often as a linear response; 3) Standard behavior, the expected "textbook" response common to agricultural lands and humid sites, and in which the runoff slope increases with increasing rainfall, and the scale of runoff far exceeds the complacent response; 4) Violent behavior, in which an abstraction threshold of 2 -6 cm clearly precedes a sudden high response; and 5) Abrupt response in which a very high portion of the rainfall is converted to event runoff without appreciable abstraction, as typified by extensively urbanized drainages. The responses and the group identifications were parameterized by a simple broken -line linear rainfall-runoff equation, and a dichotomous key based on coefficient values is proposed. Only mild associations between response type or coefficient values and the four vegetative covers (Forest, Range, Agriculture, and Urban) were found. The variety of hydrologic behavior on forested watersheds encompassed that of the other three land types.
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Grabau, Matthew R., Richard H. Hawkins, Kevin E. Verweire, and Donald C. Slack. "Variety of Antecedent Runoff Conditions for Rainfall-Runoff with the Curve Number Method." Arizona-Nevada Academy of Science, 2009. http://hdl.handle.net/10150/296695.

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Lee, Hyo Sang. "Regionalisation of rainfall-runoff models in the UK." Thesis, Imperial College London, 2006. http://hdl.handle.net/10044/1/8147.

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Freer, James E. "Uncertainty and calibration of conceptual rainfall runoff models." Thesis, Lancaster University, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.266810.

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Karlsson, Magnus Sven. "NEAREST NEIGHBOR REGRESSION ESTIMATORS IN RAINFALL-RUNOFF FORECASTING." Diss., The University of Arizona, 1985. http://hdl.handle.net/10150/282088.

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The subject of this study is rainfall-runoff forecasting and flood warning. Denote by (X(t),Y(t)) a sequence of equally spaced bivariate random variables representing rainfall and runoff, respectively. A flood is said to occur at time period (n + 1) if Y(n + 1) > T where T is a fixed number. The main task of flood warning is that of deciding whether or not to issue a flood alarm for the time period n + 1 on the basis of the past observations of rainfall and runoff up to and including time n. With each decision, warning or no warning, there is a certain probability of an error (false alarm or no alarm). Using notions from classical decision theory, the optimal solution is the decision that minimizes Bayes risk. In Chapter 1 a more precise definition of flood warning will be given. A critical review (Chapter 2) of classical methods for forecasting used in hydrology reveals that these methods are not adequate for flood warning and similar types of decision problems unless certain Gaussian assumptions are satisfied. The purpose of this study is to investigate the application of a nonparametric technique referred to as the k-nearest neighbor (k-NN) methods to flood warning and least squares forecasting. The motivation of this method stems from recent results in statistics which extends nonparametric methods for inferring regression functions in a time series setting. Assuming that the rainfall-runoff process can be cast in the framework of Markov processes then, with some additional assumptions, the k-NN technique will provide estimates that converge with an optimal rate to the correct decision function. With this in mind, and assuming that our assumptions are valid, then we can claim that this method will, as the historical record grows, provide the best possible estimate in the sense that no other method can do better. A detailed description of the k-NN estmator is provided along with a scheme for calibration. In the final chapters, the forecasts of this new method are compared with the forecasts of several other methods commonly used in hydrology, on both real and simulated data.
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Goyen, Allan. "Spatial and temporal effects on urban rainfall/runoff modeling." Online version, 2000. http://hdl.handle.net/2100/626.

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University of Technology, Sydney. Faculty of Engineering.
Although extensive worldwide literature on urban stormwater runoff exists, very few publications describe runoff development in terms of its basic building blocks or processes and their individual and accumulative significance in response to varying inputs and boundary conditions. Process algorithms should respond accurately to varying input magnitudes and characteristics as well as to changes in antecedent conditions. The present state of estimation errors involved in many current numerical simulation techniques has been reviewed in this thesis. A significant amount of errors that are presently encountered for have been explained in terms of undefined process response not explicitly included within many modelling methodologies. Extensive field monitoring of intra-catchment rainfall and runoff within an urban catchment at Giralang in Canberra, which is typical of Australian urban catchments, was carried out over a 3-year period to define and measure individual runoff processes. This monitoring work led to a greater understanding of the processes driving the aggregation of local runoff from many sub-areas into the runoff observed at full catchment scale. The results from the monitoring process prompted a number of approaches to potentially reduce standard errors of estimate from model-attributable errors based on improvements to definable catchment response mechanisms. The research isolated a number of basic building blocks associated with typical residential allotments, that can be grouped into roof drainage, yard drainage and adjacent road drainage. A proposed modelling approach was developed that allowed these building blocks at an allotment scale to be simply computed using storage routing techniques. This then aggregated via the total catchment’s public drainage system isochronal characteristics utilising a “process tree” approach to provide full catchment scale runoff response. The potential reduction in estimation errors utilising the developed procedure was assessed using a large number of recorded events from the Giralang catchment monitoring data. The proposed numerical modelling approach was found to provide significant improvements over current methods and offered a scale-independent and stormindependent methodology to model catchments of any size without the need for changes to any of the runoff routing parameters. Additionally the approach permits the flexible sequencing and inclusion of a wide range of different urban drainage structures within a catchment that are representative of the local characteristics. The developed procedure also includes a spatially varied water balance approach to infiltration estimation that is more suited to future continuous simulation models. The developed “flexible process tree” approach provides an important step forward in the numerical modelling of complex urban drainage systems. This can reduce errors of estimate by improving intra-catchment process representation.
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Books on the topic "Rainfall-runoff"

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Beven, Keith. Rainfall-Runoff Modelling. Chichester, UK: John Wiley & Sons, Ltd, 2012. http://dx.doi.org/10.1002/9781119951001.

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Loague, Keith M. Rainfall-runoff modelling. Wallingford, UK: IAHS Press, 2010.

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Wong, Tommy S. W. Kinematic-wave rainfall-runoff formulas. Hauppauge, NY: Nova Science Publishers, 2009.

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Beven, K. J. Rainfall-runoff modelling: The primer. 2nd ed. Hoboken: Wiley, 2011.

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Hromadka, Theodore V., and Robert J. Whitley. Stochastic Integral Equations and Rainfall-Runoff Models. Berlin, Heidelberg: Springer Berlin Heidelberg, 1989. http://dx.doi.org/10.1007/978-3-642-49309-6.

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E, Johnson Lynn, Cooperative Institute for Research in the Atmosphere (Fort Collins, Colo.), and Forecast Systems Laboratory (U.S.), eds. F2D: A kinematic distributed rainfall-runoff model. Boulder, Colo: U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, Oceanic and Atmospheric Research Laboratories, Forecast Systems Laboratory, 2000.

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E, Johnson Lynn, Cooperative Institute for Research in the Atmosphere (Fort Collins, Colo.), and Forecast Systems Laboratory (U.S.), eds. F2D: A kinematic distributed rainfall-runoff model. Boulder, Colo: U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, Oceanic and Atmospheric Research Laboratories, Forecast Systems Laboratory, 2000.

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Hromadka, Theodore V. Stochastic integral equations and rainfall-runoff models. Berlin: Springer-Verlag, 1989.

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Hromadka, Theodore V. Stochastic Integral Equations and Rainfall-Runoff Models. Berlin, Heidelberg: Springer Berlin Heidelberg, 1989.

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E, Johnson Lynn, Cooperative Institute for Research in the Atmosphere (Fort Collins, Colo.), and Forecast Systems Laboratory (U.S.), eds. F2D: A kinematic distributed rainfall-runoff model. Boulder, Colo: U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, Oceanic and Atmospheric Research Laboratories, Forecast Systems Laboratory, 2000.

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Book chapters on the topic "Rainfall-runoff"

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Hromadka, Theodore V., and Robert J. Whitley. "Rainfall-Runoff Aproximation." In Stochastic Integral Equations and Rainfall-Runoff Models, 1–116. Berlin, Heidelberg: Springer Berlin Heidelberg, 1989. http://dx.doi.org/10.1007/978-3-642-49309-6_1.

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Remesan, Renji, and Jimson Mathew. "Data Based Rainfall-Runoff Modelling." In Hydrological Data Driven Modelling, 151–82. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-09235-5_6.

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Belarbi, Halima, Bénina Touaibia, Nadir Boumechra, Chérifa Abdelbaki, and Sakina Amiar. "Analysis of the Hydrological Behavior of Watersheds in the Context of Climate Change (Northwestern Algeria)." In Natural Disaster Science and Mitigation Engineering: DPRI reports, 143–79. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-2904-4_5.

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AbstractThe aim of this work is to study the temporal evolution of the rainfall-runoff relations of four basins in northwestern Algeria: the Tafna Maritime, Isser Sikkak, downstream Mouilah and Upper Tafna basins. The adopted approach consists of analyzing hydroclimatic variables using statistical methods and testing the nonstationarity of the rainfall-runoff relation by the cross-simulation method using the GR2M model. The results of the different statistical methods applied to the series of rainfall and hydrometric variables show a decrease due to a break in stationarity detected since the mid-1970s and the beginning of the 1980s. The annual rainfall deficits reached average values of 34.6% during the period of 1941–2006 and 29.1% during the period of 1970–2010. The average annual wadi flows showed average deficits of 61.1% between 1912 and 2000 and 53.1% between 1973 and 2009. The GR2M conceptual model simulated the observed hydrographs in an acceptable manner by providing calculated runoff values in the calibration and validation periods greater or less than the observed runoff values. The application of the cross-simulation method highlighted the nonstationarity of the rainfall-runoff relations in three of the four studied basins, indicating downward trends of monthly runoff.
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Colosimo, C., and G. Mendicino. "GIS for Distributed Rainfall — Runoff Modeling." In Geographical Information Systems in Hydrology, 195–235. Dordrecht: Springer Netherlands, 1996. http://dx.doi.org/10.1007/978-94-015-8745-7_8.

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Naresh, Aadhi, Harish Gupta, Mudavath Gopal Naik, Sandeep Hamsa, Manne Mohan Raju, and Dinesh C. S. Bisht. "Rainfall-runoff modeling using SWAT model." In Advances in Mathematical and Computational Modeling of Engineering Systems, 183–201. Boca Raton: CRC Press, 2023. http://dx.doi.org/10.1201/9781003367420-8.

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Hromadka, Theodore V., and Robert J. Whitley. "Rainfall-Runoff Model Criterion Variable Frequency Distributions." In Stochastic Integral Equations and Rainfall-Runoff Models, 262–325. Berlin, Heidelberg: Springer Berlin Heidelberg, 1989. http://dx.doi.org/10.1007/978-3-642-49309-6_5.

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Hromadka, Theodore V., and Robert J. Whitley. "Probability and Statistics Review." In Stochastic Integral Equations and Rainfall-Runoff Models, 117–68. Berlin, Heidelberg: Springer Berlin Heidelberg, 1989. http://dx.doi.org/10.1007/978-3-642-49309-6_2.

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Hromadka, Theodore V., and Robert J. Whitley. "Introduction to Stochastic Integral Equations in Rainfall-Runoff Modeling." In Stochastic Integral Equations and Rainfall-Runoff Models, 169–214. Berlin, Heidelberg: Springer Berlin Heidelberg, 1989. http://dx.doi.org/10.1007/978-3-642-49309-6_3.

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Hromadka, Theodore V., and Robert J. Whitley. "Stochastic Integral Equations Applied to a Multi-Linear Rainfall-Runoff Model." In Stochastic Integral Equations and Rainfall-Runoff Models, 215–61. Berlin, Heidelberg: Springer Berlin Heidelberg, 1989. http://dx.doi.org/10.1007/978-3-642-49309-6_4.

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Hromadka, Theodore V., and Robert J. Whitley. "Using the Stochastic Integral Equation Method." In Stochastic Integral Equations and Rainfall-Runoff Models, 326–67. Berlin, Heidelberg: Springer Berlin Heidelberg, 1989. http://dx.doi.org/10.1007/978-3-642-49309-6_6.

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Conference papers on the topic "Rainfall-runoff"

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Cleveland, Theodore G., Xin He, and David B. Thompson. "Simple Rainfall Loss Models for Rainfall-Runoff Modeling." In World Environmental and Water Resources Congress 2008. Reston, VA: American Society of Civil Engineers, 2008. http://dx.doi.org/10.1061/40976(316)55.

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Habib, Emad, Ananda V. Aduvala, and Ehab A. Meselhe. "Effect of Radar-Rainfall Errors on Rainfall-Runoff Modeling." In World Environmental and Water Resources Congress 2007. Reston, VA: American Society of Civil Engineers, 2007. http://dx.doi.org/10.1061/40927(243)285.

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Gibbs, Matthew S., Graeme C. Dandy, and Holger R. Maier. "Calibration of Rainfall Runoff Models in Ungauged Catchments: Regionalization Relationships for a Rainfall Runoff Model." In World Environmental and Water Resources Congress 2008. Reston, VA: American Society of Civil Engineers, 2008. http://dx.doi.org/10.1061/40976(316)377.

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Kim, J. Y., and J. Sansalone. "Hydrodynamic Clarification of Rainfall-Runoff Particles." In World Environmental and Water Resources Congress 2007. Reston, VA: American Society of Civil Engineers, 2007. http://dx.doi.org/10.1061/40927(243)17.

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Blodgett, D. L., and J. A. Hoopes. "Impacts of Radar Indicated Rainfall on Distributed Rainfall-Runoff Modeling." In Watershed Management Conference 2010. Reston, VA: American Society of Civil Engineers, 2010. http://dx.doi.org/10.1061/41143(394)113.

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Kumar, Dhananjay, P. Parth Sarthi, and Prabhat Ranjan. "Rainfall-runoff modeling using computational intelligence techniques." In 2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI). IEEE, 2016. http://dx.doi.org/10.1109/icacci.2016.7732144.

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Zhou Zhen-min, Wang Xuechao, and Zhou Ke. "Rainfall-runoff forecast method based on GIS." In 2011 Second International Conference on Mechanic Automation and Control Engineering (MACE). IEEE, 2011. http://dx.doi.org/10.1109/mace.2011.5987467.

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Remesan, R., M. A. Shamim, D. Han, and J. Mathew. "ANFIS and NNARX based rainfall-runoff modeling." In 2008 IEEE International Conference on Systems, Man and Cybernetics (SMC). IEEE, 2008. http://dx.doi.org/10.1109/icsmc.2008.4811490.

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Patil, S., S. Patil, and W. Walunjkar. "Rainfall-runoff forecasting techniques for avoiding global warming." In 2013 International Conference on Information Communication and Embedded Systems (ICICES 2013). IEEE, 2013. http://dx.doi.org/10.1109/icices.2013.6508344.

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RAJURKAR, M. P., U. C. KOTHYARI, and U. C. CHAUBE. "DIALY RAINFALL RUNOFF MODELING USING ARTIFICIAL NEURAL NETWORK." In Proceedings of the 13th IAHRߝ;APD Congress. World Scientific Publishing Company, 2002. http://dx.doi.org/10.1142/9789812776969_0127.

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Reports on the topic "Rainfall-runoff"

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Peters, John C., and Daniel J. Easton. Runoff Simulation Using Radar Rainfall Data. Fort Belvoir, VA: Defense Technical Information Center, August 1996. http://dx.doi.org/10.21236/ada316115.

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Ogden, Fred L., and Hatim O. Sharif. Propagation of Radar-Rainfall Uncertainty in Runoff Predictions. Fort Belvoir, VA: Defense Technical Information Center, January 2001. http://dx.doi.org/10.21236/ada394770.

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Peters, John C. Application of Rainfall-Runoff Simulation for Flood Forecasting. Fort Belvoir, VA: Defense Technical Information Center, June 1993. http://dx.doi.org/10.21236/ada273140.

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Hawkins, R. H., and A. Barreto-Munoz. Wildcat5 for Windows, a rainfall-runoff hydrograph model: user manual and documentation. Ft. Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station, 2016. http://dx.doi.org/10.2737/rmrs-gtr-334.

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Hawkins, R. H., and A. Barreto-Munoz. Wildcat5 for Windows, a rainfall-runoff hydrograph model: user manual and documentation. Ft. Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station, 2016. http://dx.doi.org/10.2737/rmrs-gtr-334.

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Matus, Sean, and Daniel Gambill. Automation of gridded HEC-HMS model development using Python : initial condition testing and calibration applications. Engineer Research and Development Center (U.S.), November 2022. http://dx.doi.org/10.21079/11681/46126.

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The US Army Corps of Engineers’s (USACE) Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS) rainfall-runoff model is widely used within the research community to develop both event-based and continuous rainfall-runoff models. The soil moisture accounting (SMA) algorithm is commonly used for long-term simulations. Depending on the final model setup, 12 to 18 parameters are needed to characterize the modeled watershed’s canopy, surface, soil, and routing processes, all of which are potential calibration parameters. HEC-HMS includes optimization tools to facilitate model calibration, but only initial conditions (ICs) can be calibrated when using the gridded SMA algorithm. Calibrating a continuous SMA HEC-HMS model is an iterative process that can require hundreds of simulations, a time intensive process requiring automation. HEC-HMS is written in Java and is predominantly run through a graphical user interface (GUI). As such, conducting a long-term gridded SMA calibration is infeasible using the GUI. USACE Construction Engineering Research Laboratory (CERL) has written a workflow that utilizes the existing Jython application programming interface (API) to batch run HEC-HMS simulations with Python. The workflow allows for gridded SMA HEC-HMS model sensitivity and calibration analyses to be conducted in a timely manner.
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Wagner, Anna, Christopher Hiemstra, Glen Liston, Katrina Bennett, Dan Cooley, and Arthur Gelvin. Changes in climate and its effect on timing of snowmelt and intensity-duration-frequency curves. Engineer Research and Development Center (U.S.), August 2021. http://dx.doi.org/10.21079/11681/41402.

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Snow is a critical water resource for much of the U.S. and failure to account for changes in climate could deleteriously impact military assets. In this study, we produced historical and future snow trends through modeling at three military sites (in Washington, Colorado, and North Dakota) and the Western U.S. For selected rivers, we performed seasonal trend analysis of discharge extremes. We calculated flood frequency curves and estimated the probability of occurrence of future annual maximum daily rainfall depths. Additionally, we generated intensity-duration-frequency curves (IDF) to find rainfall intensities at several return levels. Generally, our results showed a decreasing trend in historical and future snow duration, rain-on-snow events, and snowmelt runoff. This decreasing trend in snowpack could reduce water resources. A statistically significant increase in maximum streamflow for most rivers at the Washington and North Dakota sites occurred for several months of the year. In Colorado, only a few months indicated such an increase. Future IDF curves for Colorado and North Dakota indicated a slight increase in rainfall intensity whereas the Washington site had about a twofold increase. This increase in rainfall intensity could result in major flood events, demonstrating the importance of accounting for climate changes in infrastructure planning.
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Agassi, Menahem, Michael J. Singer, Eyal Ben-Dor, Naftaly Goldshleger, Donald Rundquist, Dan Blumberg, and Yoram Benyamini. Developing Remote Sensing Based-Techniques for the Evaluation of Soil Infiltration Rate and Surface Roughness. United States Department of Agriculture, November 2001. http://dx.doi.org/10.32747/2001.7586479.bard.

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The objective of this one-year project was to show whether a significant correlation can be established between the decreasing infiltration rate of the soil, during simulated rainstorm, and a following increase in the reflectance of the crusting soil. The project was supposed to be conducted under laboratory conditions, using at least three types of soils from each country. The general goal of this work was to develop a method for measuring the soil infiltration rate in-situ, solely from the reflectance readings, using a spectrometer. Loss of rain and irrigation water from cultivated fields is a matter of great concern, especially in arid, semi-arid regions, e.g. much of Israel and vast area in US, where water is a limiting factor for crop production. A major reason for runoff of rain and overhead irrigation water is the structural crust that is generated over a bare soils surface during rainfall or overhead irrigation events and reduces its infiltration rate (IR), considerably. IR data is essential for predicting the amount of percolating rainwater and runoff. Available information on in situ infiltration rate and crust strength is necessary for the farmers to consider: when it is necessary to cultivate for breaking the soil crust, crust strength and seedlings emergence, precision farming, etc. To date, soil IR is measured in the laboratory and in small-scale field plots, using rainfall simulators. This method is tedious and consumes considerable resources. Therefore, an available, non-destructive-in situ methods for soil IR and soil crusting levels evaluations, are essential for the verification of infiltration and runoff models and the evaluation of the amount of available water in the soil. In this research, soil samples from the US and Israel were subjected to simulated rainstorms of increasing levels of cumulative energies, during which IR (crusting levels) were measured. The soils from the US were studied simultaneously in the US and in Israel in order to compare the effect of the methodology on the results. The soil surface reflectance was remotely measured, using laboratory and portable spectrometers in the VIS-NIR and SWIR spectral region (0.4-2.5mm). A correlation coefficient spectra in which the wavelength, consisting of the higher correlation, was selected to hold the highest linear correlation between the spectroscopy and the infiltration rate. There does not appear to be a single wavelength that will be best for all soils. The results with the six soils in both countries indeed showed that there is a significant correlation between the infiltration rate of crusted soils and their reflectance values. Regarding the wavelength with the highest correlation for each soil, it is likely that either a combined analysis with more then one wavelength or several "best" wavelengths will be found that will provide useful data on soil surface condition and infiltration rate. The product of this work will serve as a model for predicting infiltration rate and crusting levels solely from the reflectance readings. Developing the aforementioned methodologies will allow increased utilization of rain and irrigation water, reduced runoff, floods and soil erosion hazards, reduced seedlings emergence problems and increased plants stand and yields.
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Howard, Heidi, Chad Helmle, Raina Dwivedi, and Daniel Gambill. Stormwater Management and Optimization Toolbox. Engineer Research and Development Center (U.S.), January 2021. http://dx.doi.org/10.21079/11681/39480.

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As stormwater regulations for hydrologic and water quality control become increasingly stringent, Department of Defense (DoD) facilities are faced with the daunting task of complying with multiple laws and regulations. This often requires facilities to plan, design, and implement structural best management practices (BMPs) to capture, filter, and/or infiltrate runoff—requirements that can be complicated, contradictory, and difficult to plan. This project demonstrated the Stormwater Management Optimization Toolbox (SMOT), a spreadsheet-based tool that effectively analyzes and plans for compliance to the Energy Independence and Security Act (EISA) of 2007 pre-hydrologic conditions through BMP implementation, resulting in potential cost savings by reducing BMP sizes while simultaneously achieving compliance with multiple objectives. SMOT identifies the most cost-effective modeling method based on an installation’s local conditions (soils, rainfall patterns, drainage network, and regulatory requirements). The work first demonstrated that the Model Selection Tool (MST) recommendation accurately results in the minimum BMP cost for 45 facilities of widely varying climatic and regional conditions, and then demonstrated SMOT at two facilities.
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Gerstl, Zev, Thomas L. Potter, David Bosch, Timothy Strickland, Clint Truman, Theodore Webster, Shmuel Assouline, Baruch Rubin, Shlomo Nir, and Yael Mishael. Novel Herbicide Formulations for Conservation-Tillage. United States Department of Agriculture, June 2009. http://dx.doi.org/10.32747/2009.7591736.bard.

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The overall objective of this study was to develop, optimize and evaluate novel formulations, which reduce herbicide leaching and enhance agronomic efficacy. Numerous studies have demonstrated that CsT promotes environmental quality and enhances sustainable crop production, yet continued use of CsT-practices appears threatened unless cost effective alternative weed control practices can be found. The problem is pressing in the southern portion of the Atlantic Coastal Plain region of the eastern USA where cotton and peanut are produced extensively. This research addressed needs of the region’s farmers for more effective weed control practices for CsT systems. HUJI: CRFs for sulfentrazone and metolachlor were developed and tested based on their solubilizion in cationic micelles and adsorption of the mixed micelles on montmorillonite. A better understanding of solubilizing anionic and nonionic organic molecules in cationic micelles was reached. Both CRFs demonstrated controlled release compared to the commercial formulations. A bioassay in soil columns determined that the new sulfentrazone and metolachlor CRFs significantly improve weed control and reduced leaching (for the latter) in comparison with the commercial formulations. ARO: Two types of CRFs were developed: polymer-clay beads and powdered formulations. Sand filter experiments were conducted to determine the release of the herbicide from the CRFs. The concentration of metolachlor in the initial fractions of the effluent from the commercial formulation reached rather high values, whereas from the alginate-clay formulations and some of the powdered formulations, metolachlor concentrations were low and fairly constant. The movement of metolachlor through a sandy soil from commercial and alginate-clay formulations showed that the CRFs developed significantly reduced the leaching of metolachlor in comparison to the commercial formulation. Mini-flume and simulated rainfall studies indicated that all the CRFs tested increased runoff losses and decreased the amount of metolachlor found in the leachate. ARS: Field and laboratory investigations were conducted on the environmental fate and weed control efficacy of a commercially available, and two CRFs (organo-clay and alginate-encapsulated) of the soil-residual herbicide metolachlor. The environmental fate characteristics and weed control efficacy of these products were compared in rainfall simulations, soil dissipations, greenhouse efficacy trials, and a leaching study. Comparisons were made on the basis of tillage, CsT, and conventional, i.e no surface crop residue at planting (CT). Strip-tillage (ST), a commonly used form of CsT, was practiced. The organo-clay and commercial metolachlor formulations behaved similarly in terms of wash off, runoff, soil dissipation and weed control efficacy. No advantage of the organo-clay over the commercial metolachlor was observed. Alginate encapsulated metolachlor was more promising. The dissipation rate for metolachlor when applied in the alginate formulation was 10 times slower than when the commercial product was used inferring that its use may enhance weed management in cotton and peanut fields in the region. In addition, comparison of alginate and commercial formulations showed that ST can effectively reduce the runoff threat that is commonly associated with granular herbicide application. Studies also showed that use of the alginate CRF has the potential to reduce metolachlor leaching. Overall study findings have indicated that use of granular herbicide formulations may have substantial benefit for ST-system weed management for cotton and peanut production under Atlantic Coastal Plain conditions in the southeastern USA. Commercial development and evaluation at the farm scale appears warranted. Products will likely enhance and maintain CsT use in this and other regions by improving weed control options.
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