Добірка наукової літератури з теми "Hydrologic models"

Abstract. The impacts of climate and land-use changes make the stationary assumption in hydrology obsolete. Moreover, there is still considerable uncertainty regarding the future evolution of the Earth’s climate and the extent of the alteration of flow regimes. Climate change impact assessment in the water sector typically involves a modelling chain in which a hydrological model is needed to generate hydrologic projections from climate forcings. Considering the inherent uncertainty of the future climate, it is crucial to assess the performance of the hydrologic model over a wide range of climates and their corresponding hydrologic conditions. In this paper, numerous, contrasted, climate sequences identified by a hidden Markov model (HMM) are used in a differential split-sample testing framework to assess the robustness of a hydrologic model. The differential split-sample test based on a HMM classification is implemented on the time series of monthly river discharges in the upper Senegal River basin in West Africa, a region characterized by the presence of low-frequency climate signals. A comparison with the results obtained using classical rupture tests shows that the diversity of hydrologic sequences identified using the HMM can help with assessing the robustness of the hydrologic model.

Abstract The assessment of climate change impacts on water resources involves several methodological decisions, including choices of global climate models (GCMs), emission scenarios, downscaling techniques, and hydrologic modeling approaches. Among these, hydrologic model structure selection and parameter calibration are particularly relevant and usually have a strong subjective component. The goal of this research is to improve understanding of the role of these decisions on the assessment of the effects of climate change on hydrologic processes. The study is conducted in three basins located in the Colorado headwaters region, using four different hydrologic model structures [PRMS, VIC, Noah LSM, and Noah LSM with multiparameterization options (Noah-MP)]. To better understand the role of parameter estimation, model performance and projected hydrologic changes (i.e., changes in the hydrology obtained from hydrologic models due to climate change) are compared before and after calibration with the University of Arizona shuffled complex evolution (SCE-UA) algorithm. Hydrologic changes are examined via a climate change scenario where the Community Climate System Model (CCSM) change signal is used to perturb the boundary conditions of the Weather Research and Forecasting (WRF) Model configured at 4-km resolution. Substantial intermodel differences (i.e., discrepancies between hydrologic models) in the portrayal of climate change impacts on water resources are demonstrated. Specifically, intermodel differences are larger than the mean signal from the CCSM–WRF climate scenario examined, even after the calibration process. Importantly, traditional single-objective calibration techniques aimed to reduce errors in runoff simulations do not necessarily improve intermodel agreement (i.e., same outputs from different hydrologic models) in projected changes of some hydrological processes such as evapotranspiration or snowpack.

With the aim of suggesting some practical rules for the use of hydrological models, G. De MARSILY in his "free opinion" (Rev. Sci. Eau 1994, 7(3): 219-234) proposes a classification of hydrologic models into two categories: - models built on data (observable phenomena) and ; - models without any available observations (unobservable phenomena). He claims that for the former group of observable phenomena, models developed through a learning process as well as those based on the underlying physical laws are of the black box type. For the latter group of unobservable phenomena, he suggests that physically-based hydrologic models be developed. Physically-based hydrologic models should introduce to the phenomenological laws the correct empirical coefficients, which correspond to the proper time and space scales (GANOULIS, 1986). Well-known examples are Darcy's permeability coefficient on the macroscopic scale as derived from the Navier-Stokes equations on the local scale and the macroscopic dispersion coefficients in comparison with the local Fickian diffusion coefficients. Misuse of these models by confusing the proper time and space scales and determining the coefficients by calibration is not a sufficient reason to consider them as belonging to the black box type. Black box type hydrologic models, although very useful when data are available, remain formally empirical. They fail to give correct answers when serious constraints of unity in place, time and action are not fulfilled. Concerning the second class of models, we may notice that purely unobservable phenomena without any available data do not really exist in hydrology. In the case of very rare events and complex systems, such as radioactivity impacts and forecasting of changes on a large scale, physically-based models with adequate parameters may be used to integrate scarce information from experiments and expert opinions in a Bayesian probabilistic framework (APOSTOLAKIS, 1990). The most important feature of hydrologic models capable of describing real hydrologic phenomena, is the possibility of handling imprecision and natural variabilities. Uncertainties may be seen in two categories: aleatory or noncognitive, and epistemic or cognitive. Probabilistic hydrologic models are more suitable for dealing with aleatory uncertainties. Fuzzy logic-based models may quantify epistemic uncertainties (GANOULIS et al., 1996). The stochastic and fuzzy modeling approaches are briefly explained in this free opinion as compared to the deterministic physically-based hydrologic modeling.

Abstract. Machine learning has shown great promise for simulating hydrological phenomena. However, the development of machine-learning-based hydrological models requires advanced skills from diverse fields, such as programming and hydrological modeling. Additionally, data pre-processing and post-processing when training and testing machine learning models are a time-intensive process. In this study, we developed a python-based framework that simplifies the process of building and training machine-learning-based hydrological models and automates the process of pre-processing hydrological data and post-processing model results. Pre-processing utilities assist in incorporating domain knowledge of hydrology in the machine learning model, such as the distribution of weather data into hydrologic response units (HRUs) based on different HRU discretization definitions. The post-processing utilities help in interpreting the model's results from a hydrological point of view. This framework will help increase the application of machine-learning-based modeling approaches in hydrological sciences.

The strength and success of hydrological analysis depend upon the quantity and quality of observed data. In the recent past, the availability of advanced computing facilities and measurement techniques had a great impact on the field of hydrology, especially in hydrologic analysis and hydrologic modeling. In spite of such growth, the present hydrologic modeling has certain challenges: complexity (involving a large number of parameters), applicability to a specific region (difficult to generalize for other regions), and lack of understanding of the connection between model theories and the actual system. The general solution of simplifying the models in terms of developing a classification framework has been discussed and focused on in the present study. It will greatly help to overcome the hydrologic modeling challenges and provides a better understanding of the hydrologic process. In general, classification is a way of grouping entities which has similar characteristics. The importance of applying nonlinear dynamics and chaos methods for classification has been realized in the recent past; since such studies provide exclusive information on hidden characteristics such as complexity, nonlinearity, dimensionality, etc. Of hydrological processes. The hydrologic processes are complex. In this study, information regarding the complexity is extracted by statistical analysis and linear methods such as Autocorrelation Function, and Average Mutual Information. 367 gridded rainfall stations over Peninsular Indian basins are used to investigate the applicability of different methods used in the study.

New tools and concepts in the form of mathematical models, remote sensing and Geographic Information System (GIS), communication and telemetering have been developed for the complex hydrologic systems that permit a different analysis of processes and allow watershed to be considered as an integrated planning and management unit. Hydrological characteristics can be generated through spatial analysis, and ready for input into a distributed hydrologic models to define adequately the hydrological response of a watershed that can be related back to the specific environmental, climatic, and geomorphic conditions. In the present paper, some recent development in hydrologic modeling will be reviewed with recognition of the role of horizontal routing scheme in large scale hydrologic modeling. Among others, these developments indicated the needs of alternative horizontal routing models at grid scale level that can be coupled to land surface parameterization schemes that presently still employed the linear routing model. Non-linear routing scheme will be presented and discussed in this paper as possible extension.

Abstract. This work addresses the impact of climate change on the hydrology of a catchment in the Mediterranean, a region that is highly susceptible to variations in rainfall and other components of the water budget. The assessment is based on a comparison of responses obtained from five hydrologic models implemented for the Rio Mannu catchment in southern Sardinia (Italy). The examined models – CATchment HYdrology (CATHY), Soil and Water Assessment Tool (SWAT), TOPographic Kinematic APproximation and Integration (TOPKAPI), TIN-based Real time Integrated Basin Simulator (tRIBS), and WAter balance SImulation Model (WASIM) – are all distributed hydrologic models but differ greatly in their representation of terrain features and physical processes and in their numerical complexity. After calibration and validation, the models were forced with bias-corrected, downscaled outputs of four combinations of global and regional climate models in a reference (1971–2000) and future (2041–2070) period under a single emission scenario. Climate forcing variations and the structure of the hydrologic models influence the different components of the catchment response. Three water availability response variables – discharge, soil water content, and actual evapotranspiration – are analyzed. Simulation results from all five hydrologic models show for the future period decreasing mean annual streamflow and soil water content at 1 m depth. Actual evapotranspiration in the future will diminish according to four of the five models due to drier soil conditions. Despite their significant differences, the five hydrologic models responded similarly to the reduced precipitation and increased temperatures predicted by the climate models, and lend strong support to a future scenario of increased water shortages for this region of the Mediterranean basin. The multimodel framework adopted for this study allows estimation of the agreement between the five hydrologic models and between the four climate models. Pairwise comparison of the climate and hydrologic models is shown for the reference and future periods using a recently proposed metric that scales the Pearson correlation coefficient with a factor that accounts for systematic differences between datasets. The results from this analysis reflect the key structural differences between the hydrologic models, such as a representation of both vertical and lateral subsurface flow (CATHY, TOPKAPI, and tRIBS) and a detailed treatment of vegetation processes (SWAT and WASIM).

Floods are among the most devastating natural disasters in small suburban catchments. These phenomena, causing loss of life and massive property damage, pose a serious threat to the economy. Hydrological modeling is extremely important in terms of climate change, and the use of appropriate modeling can be a useful tool for flood risk prevention and mitigation. Rainfall–runoff modeling requires the selection of an appropriate hydrological model in order to obtain satisfactory results. Hydrological models are used in water resource planning and management to estimate catchment runoff. Small uncontrolled catchments play a particularly important role in hydrological phenomena, since changes in them affect flows in the recipient. Hydrologists are particularly interested in developing hydrological models that can be made with a minimum of data and parameters. Nash models and the Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS) are examples of simple and most practical hydrologic models. These models were used in this paper to study geographic and qualitative changes in precipitation runoff due to land cover changes. The modeling was carried out for two spatial aspects relating to the years 1940 and 2018. The model allowed for the simulation of the river flow that can occur under different rainfall probabilities. The analysis of the results was used to evaluate the hydrological models used. The hundred-year flow modeled with the Nash model for 1940 was 13.4 m3∙s−1, whereas the second model gave slightly lower flow values. In addition, modeling the flow for 2018 (after changing the land cover) highlighted the increase in the flow value for both models, where again the flow volume was slightly higher for the Nash model and amounted to about 19 m3∙s−1. The flow differences for individual models were not too large. This made it possible to conclude that the simulated outflow hydrographs are in good agreement, and this means that the models accurately reproduce the flow of the Michałówka River. The study showed that rapid urbanization adversely affects hydrological processes. In addition, the study showed that a well-distributed model can outperform a global flood forecasting model, especially in terms of magnitude, as in the current study example.

Transbasin diversions and dams allow for water uses when and where there is high demand and low supply, but can come with an expense to the environment. This paper presents a linkage of hydrologic and hydraulic modeling and datasets to assess the hydrologic and hydraulic stability within a transbasin watershed as an approach for meeting water use targets and safeguarding environmental sustainability. The approach used a Prediction in Ungauged Basin (PUB) regionalization technique that completed the parameterization of a study watershed hydrologic model by transferring calibrated parameters from a reference watershed hydrologic model. This resulted in a long-term, simulated natural flow record that was compared to the measured modified flow record for the same time period to assess flow alteration. In the sensitive reach, hydraulic modeling results tracked channel response from before hydrologic modification to baseline using repeated survey years during the hydrologic modification. The combined assessment of hydrology and hydraulics highlighted the relation between flow regime and channel form.

The combination of Hydrological Models and high-resolution Satellite Precipitation Products (SPPs) or regional Climatological Models (RCMs), has provided the means to establish baselines for the quantification, propagation, and reduction in hydrological uncertainty when generating streamflow forecasts. This study aimed to improve operational real-time streamflow forecasts for the Upper Zambezi River Basin (UZRB), in Africa, utilizing the novel Variational Ensemble Forecasting (VEF) approach. In this regard, we describe and discuss the main steps required to implement, calibrate, and validate an operational hydrologic forecasting system (HFS) using VEF and Hydrologic Processing Strategies (HPS). The operational HFS was constructed to monitor daily streamflow and forecast them up to eight days in the future. The forecasting process called short- to medium-range (SR2MR) streamflow forecasting was implemented using real-time rainfall data from three Satellite Precipitation Products or SPPs (The real-time TRMM Multisatellite Precipitation Analysis TMPA-RT, the NOAA CPC Morphing Technique CMORPH, and the Precipitation Estimation from Remotely Sensed data using Artificial Neural Networks, PERSIANN) and rainfall forecasts from the Global Forecasting System (GFS). The hydrologic preprocessing (HPR) strategy considered using all raw and bias corrected rainfall estimates to calibrate three distributed hydrological models (HYMOD_DS, HBV_DS, and VIC 4.2.b). The hydrologic processing (HP) strategy considered using all optimal parameter sets estimated during the calibration process to increase the number of ensembles available for operational forecasting. Finally, inference-based approaches were evaluated during the application of a hydrological postprocessing (HPP) strategy. The final evaluation and reduction in uncertainty from multiple sources, i.e., multiple precipitation products, hydrologic models, and optimal parameter sets, was significantly achieved through a fully operational implementation of VEF combined with several HPS. Finally, the main challenges and opportunities associated with operational SR2MR streamflow forecasting using VEF are evaluated and discussed.

The level of spatial and vertical detail of important hydrologic processes within a watershed that needs to be represented by a conceptual rainfall-runoff (CRR) model in order to accurately simulate the streamflow is not well understood. The paucity of high-resolution hydrologic information in the past guided the direction of model development to more accurately represent processes directly related to the vertical movement of moisture within the watershed rather than the spatial variability of these processes. As a result, many of the CRR models currently available are so complex (vertically), that expert knowledge of the model and watershed system is required to successfully estimate values for model parameters using manual methods. Automatic parameter estimation procedures, developed to reduce the time and effort required with manual methods, do not provide parameter estimates and hydrograph simulations that are considered acceptable by the hydrologists responsible for operational forecasting. Newly available, high-resolution hydrologic information may provide insight to the spatial variability of important rainfall-runoff processes. However, effective and efficient methods to incorporate the data into the current modeling strategies need to be developed. This work describes a new hybrid multicriteria calibration approach that combines the strength of automatic and manual calibration methods. The new approach was used to investigate the benefits of different levels of spatial and vertical representation of important watershed hydrologic variables with conceptual rainfall runoff models.

El principal objectiu d'aquesta investigació és estudiar la dinàmica hidrològica d'una conca Mediterrània
afectada per canvis d'ús del sòl, mitjançant el monitoreig d'aquest i de l'aigua superficial. Aquest
objectiu s'ha treballat a partir mesuraments de components del balanç hídric pels diferents tipus de
cobertura i sòl, amb règims d'humitat i temperatura de transició.
Aquest estudi s'ha realitzat a la conca de la Ribera Salada (Prepirineu meridional Català, al NE
d'Espanya), amb una extensió de 222.5 km2, i un interval altitudinal de 420 a 2385 m i predomini de
pendents entre 12 - 25 % i 25 - 50 %. El substrat consisteix en conglomerats calcaris massius, calcilutites
i llims. La precipitació es de 507 i 763 mm. Amb sòls poc profunds, calcaris i pedregosos, essent
majoritàriament Inceptisòls (Typic Calciusteps, Typic Haploustepts) i Entisòls (Typic Ustifluvents, Typic
Udorthortents). A les zones més elevades de la conca, els sòls són més humits, degut a l'augment de la
precipitació, on es produeixen processos de descarbonatació del sòl. L'ús del sòl és majoritàriament
forestal, amb presència d'ecosistemes de ribera, subalpins i vegetació submediterrània. Algunes àrees es
troben amb cultius de patata, cereal i pastures. Una de les característiques més importants d'aquesta
conca són els canvis d'ús del sòl que ha patit en els últims 50 anys degut a l'abandó dels masos i cultius
tradicionals. Es seleccionaren vuit llocs de mostreig considerant les següents cobertes: Quercus ilex, bosc
de ribera, Pinus sylvestris, pastures, cultius (cereal-patata) i Pinus uncinata. A partir de l'any 1997 fins el
2005, s'han anat monitorejant el contingut d'humitat del sòl, l'escolament i els cabals. Des del 2004 s'han
anat anotant dades de drenatge. Les variables meteorològiques es mesuren a l'estació de Lladurs de la
XAC (Xarxa Agrometeorològica de Catalunya).
Els resultats obtenguts durant tres anys mostren una domini del règim d'humitat ústic (SSS, 2006), o xèric
en aquells anys més secs. En la modelització de règims d'humitat i temperatura del sòl, s'utilitzaren els
models de simulació NSM "Newhall simulation model" (Newhall, 1976) i JSM "Jarauta simulation
model" (Jarauta 1989). NSM (Newhall,1976) tendeix a sobre estimar el règim d'humitat del sòl, però
JSM (Jarauta, 1989) simula correctament el règim d'humitat del sòl (SSS, 2006) de la conca, funcionant
millor en condicions intermitges d'humitat del sòl. Ambdós models simulen correctament el règim de
temperatura dels sòls. Predomina un règim de temperatura mèsic-tèrmic, amb tendència a tèrmic els anys
secs. A petita escala la profunditat del sòl, pendent, pedregositat i una alta porositat del sòl són factores
que varien el règim d'humitat del sòl. La informació de sòl i clima, complementada mitjançant SIG, va
permetre l'obtenció de mapes de règim d'humitat del sòl de la conca, a escala 1:50000, els quals
permeten establir mediante simució els règims d'humitat del sòl en diferents escenaris de canvis
meteorològics.
El model TOPLATS ha sigut utilitzat en l'estimació de l'humitat del sòl en diferents usos del sòl. Aquest
model fou calibrat amb les equacions del filtre Kalman estès (EKF), que deriven de la minimització del
quadrat de la diferència entre els valors reals i els estimats (Goegebeur & Pauwels, 2007). Aquesta
metodologia interrelaciona correctament els valors de pluja, humitat del sòl, escolament i infiltració,
essent els valors d'humitat els que més s'aproximen als reals. Els resultats mostren que aquest filtre és
una eina útil per estimar el volum d'aigua del sòl emmagatzemada en conques a escala puntual,
assegurant una aplicació correcta del model hidrològic.
Per la modelització del comportament de l'humitat del sòl i diferents components del balanç hídric
s'utilitzà el modelo TOPLATS (Famiglietti & Wood, 1994). El model de simulació TOPLATS permite
simulà acceptablement el comportament de l'humitat del sòl. Els resultats de infiltració, escolament,
intercepció, evapotranspiració de referència i temperatura del sòl són correctes. Les diferències existents
entre valors simulats i observats són: l'humitat del sòl no sobrepassa el 5%, la infiltració fluctua entre 4%
i 15%, la diferència entre els valors reals i simulats d'evapotranspiració, depèn de l'estació de l'any,
essent 1mm a l'hivern i 2.7 mm a l'estiu. La temperatura varia entre 0.01ºC i 3.5ºC. El model calibrat
prediu amb precisió el comportament de les diferents components del balanç hídric. Respecte als valors
mesurats d'aigua de drenatge correspon al 11-41 % de la pluja total.
Respecte al balanç d'aigua en el sòl (ΔSW), els valors són negatius durant cert període de l'any, arribant a
valors crítics els mesos secs. La recuperació de humitat del sòl durant la resta de mesos succeeix de
manera parcial. A la part mitja de la conca, alguns mesos els valors d'humitat del sòl s'acosten a
condicions de punt de marchites (ecosistema submediterrani). A la part alta de la conca el sòl conserva
humitat (ecosistema subalpí). Els valors de cabal trobats corresponen a aportacions per escolament el
cuals són molt baixos. La majoria de les sortides es deuen a evapotranspiració, intercepció, infiltració i
drenatge (en ordre de importància).
El principal objetivo de esta investigación es estudiar la dinámica hidrológica de una cuenca Mediterránea
afectada por los cambios de uso del suelo, mediante el monitoreo del suelo y el agua superficial. Dicho objetivo
se ha abordado a partir de la medición de componentes del balance hídrico para diferentes tipos de cobertura y
suelo, considerando regimenes de humedad y temperatura de transición.
Este estudio se ha realizado en la cuenca de la Ribera Salada (Prepirineo meridional Catalán, NE España) de
222.5 km2, con un intervalo altitudinal de 420 a 2385 m y predominio de pendientes entre 12 - 25 % y 25 - 50
%. El sustrato consiste en conglomerados calcáreos masivos, calcilutitas y limos. La precipitación anual es de
507 y 763 mm. Los suelos són poco profundos, calcáreos y pedregosos, siendo en su mayoría Inceptisols
(Typic Calciusteps, Typic Haploustepts) y Entisols (Typic Ustifluvents, Typic Udorthortents). En las partes
altas de la cuenca los suelos son más húmedos, debido al aumento de la precipitación, allí ocurren procesos de
descarbonatación del suelo. Predomina el uso forestal, con ecosistemas de ribera, subalpinos y vegetación
submediterránea. Algunas áreas se dedican al cultivo de patatas, cereal y pastos. Una de las características más
importantes de esta cuenca es los importantes cambios de uso del suelo sufridos en los últimos 50 años, debido
al abandono de las masías y cultivos tradicionales.
Se seleccionaron ocho sitios de muestreo, considerando las siguientes coberturas: Quercus ilex, bosque de
ribera, Pinus sylvestris, pastos, cultivo (cereal-patata) y Pinus uncinata. A partir del año 1997 hasta 2005, se
han venido monitoreando el contenido de humedad del suelo, escorrentía y caudales. Desde 2004 se vienen
tomando datos drenaje. Las variables meteorológicas se miden la estación Lladurs perteneciente a la XAC
(Xarxa Agrometeorológica de Cataluña).
Los resultados obtenidos par un period de tres años muestran una predominancia del regimen de humedad
ústico (SSS, 2006), o xérico en los años más secos. Se utilizaron los modelos de simulación NSM "Newhall
simulation model" (Newhall, 1976) y JSM "Jarauta simulation model" (Jarauta 1989) en la modelización de
regimenes de humedad y temperatura del suelo. NSM (Newhall,1976) tiende a sobre estimar el régimen de
humedad del suelo. Por contra, JSM (Jarauta, 1989) simula de forma correcta el régimen de humedad del suelo
(SSS, 2006) presente en la cuenca, funcionando mejor bajo condiciones medias de humedad del suelo. Ambos
modelos simulan de forma correcta el régimen de temperatura de los suelos. Predomina un régimen de
temperatura mésico-térmico, con tendencia a térmico para los años secos. A pequeña escala la profundidad del
suelo, pendiente, pedregosidad y alta porosidad del suelo son factores que hacen variar el régimen de humedad
del suelo. La información de suelo y clima, complementada mediante SIG, permitió obtener mapas de régimen
de humedad del suelo para la cuenca, a una escala 1:50000, los cuales permiten establecer mediante simulación
los regimenes de humedad en el suelo bajo diferentes escenarios de cambios meteorológicos.
El modelo TOPLATS ha sido utilizado en la estimación de la humedad en el suelo para diferentes usos del
suelo. Este modelo fue calibrado con las ecuaciones del filtro Kalman extendido (EKF), que se derivan de la
minimización del cuadrado de la diferencia entre los valores reales y los estimados (Goegebeur & Pauwels,
2007). Esta metodología interrelaciona correctamente los valores de lluvia, humedad en el suelo, escorrentía y
infiltración, siendo los valores de humedad los mas ajustados a los valores reales. Los resultados muestran que
este filtro es una herramienta para estimar el volumen de agua en el suelo almacenada en las cuencas a escala
puntual, asegurando una aplicación correcta del modelo hidrológico.
Para la modelización del comportamiento de la humedad del suelo y los diferentes componentes del balance
hídrico se utilizó el modelo TOPLATS (Famiglietti & Wood, 1994). El modelo de simulación TOPLATS
permite simular aceptablemente el comportamiento de la humedad del suelo. Los resultados para infiltración,
escorrentía, intercepción, evapotranspiración de referencia y temperatura del suelo son correctos. Las
diferencias existentes entre valores simulados y observados son: la humedad del suelo no sobrepasa el 5%, la
infiltración fluctúa entre 4% y 15%, la diferencia entre los valores reales y simulados de evapotranspiración,
depende de la estación del año, siendo 1mm en invierno y 2.7 mm en verano, la temperatura varia entre 0.01 ºC
y 3.5ºC. El modelo calibrado predice con precisión el comportamiento de las diferentes componentes del
balance hídrico. Respecto a los valores medidos para agua de drenaje corresponde al 11-41 % de la lluvia total.
Respecto al balance de agua en el suelo (ΔSW), los valores son negativos para un corto periodo del año,
alcanzando valores críticos en meses secos. La recuperación de humedad del suelo para el resto de los meses
ocurre de manera parcial. En la parte media de la cuenca, para algunos meses los valores de humedad del suelo
son cercanos a condiciones de punto de marchites permanente (ecosistema submediterráneo). En la parte alta
de la cuenca el suelo conserva condiciones intermedias de humedad (ecosistema subalpino). Los valores de
caudal encontrados corresponden a los aportes por escorrentía, los cuales son muy bajos. La mayor parte de las
salidas ocurren por evapotranspiración, intercepción, infiltración y drenaje (en orden de importancia).
The main aim of this research is to study the hydrological dynamics of a Mediterranean mountain basin
affected by land use changes, by means of the monitoring of soil and surface water. This aim has been
reached by measuring and simulating hydric balance components of different soils and under different
vegetational types, considering water and temperature transition regimes.
This research was done in Ribera Salada basin (Catalan Pre Pyrenees, NE Spain), with an area of 222.5
km2, altitudes between 420 and 2385 m, with predominance slopes between 12 - 25 % and 25 - 50 %. The
substrate consists of massive calcareous conglomerates, calcilutites and limestones. Main annual
precipitation are 507 to 763 mm. Soils are shallow, calcareous and stony, being most of them Inceptisols
(Typic Calciusteps, Typic Haploustepts) and Entisols (Typic Ustifluvents, Typic Udorthortents). In the
upper and moister part of the basin soil decarbonatation takes place. Forest use is predominant, going
from brook forest environments to subalpine and submediterranean vegetation. Agricultural uses include
mainly the growing of cereals, potatoes and pastures. One of the most important characteristics in this
basin are the significant soil use changes in the last 50 years, due to the abandonment of farms and
traditional crops.
Eight sites were studied, corresponding to soils under Quercus ilex, brook forest, Pinus sylvestris, pasture,
crops (cereal-potatoes) and Pinus uncinata. From 1997 until 2005, soil moisture, run-off, water flow and
interception were monitored. From 2004 on, drainage data has been recorded. Meteorological variables
were measured by means of a complete Lladurs meteorological station, belonging to XAC (Catalan
Agrometeorological Network).
The obtained results to three years show the predominance of ustic moisture regime (SSS, 2006), or xeric
during the driest years. The simulation models NSM "Newhall simulation model" (Newhall, 1976) and
JSM "Jarauta simulation model" (Jarauta 1989) were used to represent soil moisture and temperature
regimes. NSM estimates a higher level of soil moisture regimes than observed. On the contrary, JSM
simulates correctly soil moisture regimes, working better under intermediate soil moisture conditions.
Both models simulate correctly the soil temperature regimes, being mesic-thermic to thermic during the
driest years. At detailed scale (plot observation), soil depth, slope, stone amount and high soil porosity are
factors that affect the soil moisture regimes. Soil and climate information, implemented through a GIS,
allowed us to obtain soil moisture regime maps of the basin at a 1:50000 scale, which are very useful to
simulate soil moisture regimes in different scenarios of meteorological changes.
The TOPLATS model, when used to estimate soil moisture under different cover types, was calibrated
with Extend Kalman filter (EKF) equations derived through a minimization of the square difference
between the true and estimated model state (Goegebeur & Pauwels, 2007). This methodology interrelates
correctly rainfall, soil moisture, runoff and infiltration. Among them, the obtained soil moisture values
corresponded the best to observed data. The results show that it is a useful tool to estimate soil water
volume stored in basins at a point scale, ensuring a correct application of this hydrological model.
To model soil moisture behaviour and the different hydric balance components, the TOPLATS model
(Famiglietti & Wood, 1994) was used. TOPLATS model simulates correctly the soil moisture behaviour.
The differences between observed and simulated values are the following: soil moisture does not surpass
5%; the infiltration fluctuates between 4% to 15%; in evapotraspiration depends on the season being
between 1 mm in winter to 2.7 mm in summer, soil temperature values difference fluctuates between
0.01ºC and 3.5ºC.The calibrated model predicts precisely the behaviour of different hydric balance
components. The measured water drainage amount is 11-41 % of total rain.
The observed and simulated soil water storage in the basin (ΔSW), has negative values during the driest
months. Soil moisture recovery during the rest of the months is only partial. In the medium part of the
basin, occupied by submediterranean ecosystems, soil moisture values are closer to drought conditions
during some months of the year. In the highest part of the basin (subalpine ecosystems) there are
intermediate soil moisture conditions in dry periods. Most part of water outputs are due to
evapotranspiration, interception, infiltration and drainage, in decreasing order of importance. Run-off
values are very low.

Thesis (Ph. D.)--Ohio State University, 2003.
Title from first page of PDF file. Document formatted into pages; contains xvi, 378 p.; also includes graphics (some col.). Includes bibliographical references (p. 229-252). Available online via OhioLINK's ETD Center

Accurate streamflow prediction is critical for ensuring water supply and detecting floods, while also providing essential hydrological inputs for other scientific models in fields such as climate and agriculture. Recently, deep learning models have been shown to achieve state-of-the-art regionalization performance by building a global hydrologic model. These models predict streamflow given catchment physical characteristics and weather forcing data. However, these models are only focused on gauged basins and cannot adapt to ungaugaed basins, i.e., basins without training data. Prediction in Ungauged Basins (PUB) is considered one of the most important challenges in hydrology, as most basins in the United States and around the world have no observations. In this work, we propose a meta-transfer learning approach by enhancing imperfect physics equations that facilitate model adaptation. Intuitively, physical equations can often be used to regularize deep learning models to achieve robust regionalization performance under gauged scenarios, but they can be inaccurate due to the simplified representation of physics. We correct such uncertainty in physical equation by residual approximation and let these corrected equations guide the model training process. We evaluated the proposed method for predicting daily streamflow on the catchment attributes and meteorology for large-sample studies (CAMELS) dataset. The experiment results on hydrological data over 19 years demonstrate the effectiveness of the proposed method in ungauged scenarios.

The ability to simulate snow accumulation and melting processes is fundamental to developing real-time hydrological models in watersheds with a snowmelt-dominated flow regime. A primary source of uncertainty with this model development approach is the subjectivity related to which historical periods to use and how to combine parameters from multiple calibration events. The Hydrologic Engineering Center, Hydrological Modeling System, has recently implemented a hybrid temperature index (TI) snow module that has not been extensively tested. This study evaluates a radiatative temperature index (RTI) model’s performance relative to the traditional air TI model. The TI model for Willow Creek performed reasonably well in both the calibration and validation years. The results of the RTI calibration and validation simulations resulted in additional questions related to how best to parameterize this snow model. An RTI parameter sensitivity analysis indicates that the choice of calibration years will have a substantial impact on the parameters and thus the streamflow results. Based on the analysis completed in this study, further refinement and verification of the RTI model calculations are required before an objective comparison with the TI model can be completed.

The risk of pluvial flooding is going to increase as climate change causes an increase in intense precipitation along with urbanisation leading to an increase in impermeable surfaces. In the last decade, cities such as Malmö and Copenhagen have already experienced severe pluvial flooding that has caused extensive damage. Adapting to climate change by creating flood resilient urban areas is therefore important and blue-green infrastructure (BGI) may be one measure to accomplish this. A hydrological model called TFM-DYN has been used to investigate whether BGI can aid the mitigation of pluvial flooding. TFM-DYN can also assist in selecting the best locations of BGIs. The problem of modeling urban floods using distributed high resolution hydrological models while considering the hydrological process in the upstream area is difficult due to the limited current computation capacity. However, coupling a distributed hydrological model (TFM-DYN) with an other semi distributed models (HYPE) is crucial to enable simulate, predict and map floods with high-resolution for an urban area while considering its catchment area. With the using of the new suggested coupled hydrological model, it is possible to connect and use the output results from HYPE model as an input to a distributed model (TFM-DYN). The interaction between HYPE and TFM-DYN will consider the hydrologic process occurred outside the model boundary of the interested urban area. The coupling of the two models will help initiating the model with real water depth data that may lead to more realistic simulation. The procedure of input data manipulation using the two model interactions is explained in details. The model is tested on a selected urban area to dynamically simulate the changes in the water depth with time using high resolution gridded data. The new coupled model can be of a great tool for wide range of user and stakeholders as an example to municipalities, water experts, insurance companies and to all other interested water organizations who have access to regional catchment models and in need for a high-resolution, flood simulation and mapping model.

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.

The proliferation of continuous streamflow monitoring and spatial data suitable for hydraulic modeling is increasing opportunities to use hydraulic habitat analysis to inform ecological models. However, species population and streamflow data exhibit high variability, making it challenging to identify hydrologic and hydraulic metrics that effectively correlate with ecological outcomes. Metric selection presents a challenge for informing environmental flow decisions and adaptive management of water infrastructure. This study applies models to characterize environmental flows with in-creasing model complexity, including the use of hydraulic models to estimate suitable habitat areas at a given flow. The results are compared to field-measured fish outcomes over the same period using functional data analysis. The variance in model correlation with ecological outcomes aids in identifying the most effective environmental flow parameters while also indicating potential pitfalls from increasing model complexity. This analysis demonstrates techniques that synthesize environmental flows with available habitat analysis and validates the approach. The case study is based on the Rio Grande silvery minnow (Hybognathus amarus, minnow), an endangered fish species in the Middle Rio Grande. Analysis focused on different methods to quantify spring runoff coinciding with the inundation of floodplain nursery habitat necessary for the minnow’s larval and juvenile life stages.