Dynamic hydrological modeling in drylands with TRMM based rainfall

This paper introduces and evaluates DryMOD, a dynamic water balance model of the key hydrological process in drylands that is based on free, public-domain datasets. The rainfall model of DryMOD makes optimal use of spatially disaggregated Tropical Rainfall Measuring Mission (TRMM) datasets to simulate hourly rainfall intensities at a spatial resolution of 1-km. Regional-scale applications of the model in seasonal catchments in Tunisia and Senegal characterize runoff and soil moisture distribution and dynamics in response to varying rainfall data inputs and soil properties. The results highlight the need for hourly-based rainfall simulation and for correcting TRMM 3B42 rainfall intensities for the fractional cover of rainfall (FCR). Without FCR correction and disaggregation to 1 km, TRMM 3B42 based rainfall intensities are too low to generate surface runoff and to induce substantial changes to soil moisture storage. The outcomes from the sensitivity analysis show that topsoil porosity is the most important soil property for simulation of runoff and soil moisture. Thus, we demonstrate the benefit of hydrological investigations at a scale, for which reliable information on soil profile characteristics exists and which is sufficiently fine to account for the heterogeneities of these. Where such information is available, application of DryMOD can assist in the spatial and temporal planning of water harvesting according to runoff-generating areas and the runoff ratio, as well as in the optimization of agricultural activities based on realistic representation of soil moisture conditions.

Meteomap: Generation Of Meteorological Variables For Distributed Physically-Based Hydrological Modeling

Distributed energy and water balance models require time-series surfaces of the meteorological variables involved in hydrological processes. Most of the hydrological GIS-based models apply simple interpolation techniques to extrapolate the point scale values registered at weather stations at a watershed scale. In mountainous areas, where the monitoring network ineffectively covers the complex terrain heterogeneity, simple geostatistical methods for spatial interpolation are not always representative enough, and algorithms that explicitly or implicitly account for the features creating strong local gradients in the meteorological variables must be applied. Originally developed as a meteorological pre-processing tool for a complete hydrological model (WiMMed), MeteoMap has become an independent software. The individual interpolation algorithms used to approximate the spatial distribution of each meteorological variable were carefully selected taking into account both, the specific variable being mapped, and the common lack of input data from Mediterranean mountainous areas. They include corrections with height for both rainfall and temperature (Herrero et al., 2007), and topographic corrections for solar radiation (Aguilar et al., 2010). MeteoMap is a GIS-based freeware upon registration. Input data include weather station records and topographic data and the output consists of tables and maps of the meteorological variables at hourly, daily, predefined rainfall event duration or annual scales. It offers its own pre and post-processing tools, including video outlook, map printing and the possibility of exporting the maps to images or ASCII ArcGIS formats. This study presents the friendly user interface of the software and shows some case studies with applications to hydrological modeling.

Integrated sensitivity analysis, calibration, and uncertainty propagation analysis approaches for supporting hydrological modeling

The successful performance of a hydrological model is usually challenged by the quality of the sensitivity analysis, calibration and uncertainty analysis carried out in the modeling exercise and subsequent simulation results. This is especially important under changing climatic conditions where there are more uncertainties associated with climate models and downscaling processes that increase the complexities of the hydrological modeling system. In response to these challenges and to improve the performance of the hydrological models under changing climatic conditions, this research proposed five new methods for supporting hydrological modeling. First, a design of experiment aided sensitivity analysis and parameterization (DOE-SAP) method was proposed to investigate the significant parameters and provide more reliable sensitivity analysis for improving parameterization during hydrological modeling. The better calibration results along with the advanced sensitivity analysis for significant parameters and their interactions were achieved in the case study. Second, a comprehensive uncertainty evaluation scheme was developed to evaluate three uncertainty analysis methods, the sequential uncertainty fitting version 2 (SUFI-2), generalized likelihood uncertainty estimation (GLUE) and Parameter solution (ParaSol) methods. The results showed that the SUFI-2 performed better than the other two methods based on calibration and uncertainty analysis results. The proposed evaluation scheme demonstrated that it is capable of selecting the most suitable uncertainty method for case studies. Third, a novel sequential multi-criteria based calibration and uncertainty analysis (SMC-CUA) method was proposed to improve the efficiency of calibration and uncertainty analysis and control the phenomenon of equifinality. The results showed that the SMC-CUA method was able to provide better uncertainty analysis results with high computational efficiency compared to the SUFI-2 and GLUE methods and control parameter uncertainty and the equifinality effect without sacrificing simulation performance. Fourth, an innovative response based statistical evaluation method (RESEM) was proposed for estimating the uncertainty propagated effects and providing long-term prediction for hydrological responses under changing climatic conditions. By using RESEM, the uncertainty propagated from statistical downscaling to hydrological modeling can be evaluated. Fifth, an integrated simulation-based evaluation system for uncertainty propagation analysis (ISES-UPA) was proposed for investigating the effects and contributions of different uncertainty components to the total propagated uncertainty from statistical downscaling. Using ISES-UPA, the uncertainty from statistical downscaling, uncertainty from hydrological modeling, and the total uncertainty from two uncertainty sources can be compared and quantified. The feasibility of all the methods has been tested using hypothetical and real-world case studies. The proposed methods can also be integrated as a hydrological modeling system to better support hydrological studies under changing climatic conditions. The results from the proposed integrated hydrological modeling system can be used as scientific references for decision makers to reduce the potential risk of damages caused by extreme events for long-term water resource management and planning.

Areal rainfall estimation using moving cars - computer experiments including hydrological modeling

The need for high temporal and spatial resolution precipitation data for hydrological analyses has been discussed in several studies. Although rain gauges provide valuable information, a very dense rain gauge network is costly. As a result, several new ideas have been emerged to help estimating areal rainfall with higher temporal and spatial resolution. Rabiei et al. (2013) observed that moving cars, called RainCars (RCs), can potentially be a new source of data for measuring rainfall amounts. The optical sensors used in that study are designed for operating the windscreen wipers and showed promising results for rainfall measurement purposes. Their measurement accuracy has been quantified in laboratory experiments. Considering explicitly those errors, the main objective of this study is to investigate the benefit of using RCs for estimating areal rainfall. For that, computer experiments are carried out, where radar rainfall is considered as the reference and the other sources of data, i.e. RCs and rain gauges, are extracted from radar data. Comparing the quality of areal rainfall estimation by RCs with rain gauges and reference data helps to investigate the benefit of the RCs. The value of this additional source of data is not only assessed for areal rainfall estimation performance, but also for use in hydrological modeling. The results show that the RCs considering measurement errors derived from laboratory experiments provide useful additional information for areal rainfall estimation as well as for hydrological modeling. Even assuming higher uncertainties for RCs as obtained from the laboratory up to a certain level is observed practical.

Hydrological simulation using SWAT model in headwater basin in Southeast Brazil

Hydrological models are important tools that have been used in water resource planning and management. Thus, the aim of this work was to calibrate and validate in a daily time scale, the SWAT model (Soil and Water Assessment Tool) to the watershed of the Galo creek , located in Espírito Santo State. To conduct the study we used georeferenced maps of relief, soil type and use, in addition to historical daily time series of basin climate and flow. In modeling were used time series corresponding to the periods Jan 1, 1995 to Dec 31, 2000 and Jan 1, 2001 to Dec 20, 2003 for calibration and validation, respectively. Model performance evaluation was done using the Nash-Sutcliffe coefficient (E NS) and the percentage of bias (P BIAS). SWAT evaluation was also done in the simulation of the following hydrological variables: maximum and minimum annual daily flowsand minimum reference flows, Q90 and Q95, based on mean absolute error. E NS and P BIAS were, respectively, 0.65 and 7.2% and 0.70 and 14.1%, for calibration and validation, indicating a satisfactory performance for the model. SWAT adequately simulated minimum annual daily flow and the reference flows, Q90 and Q95; it was not suitable in the simulation of maximum annual daily flows.

Prediction Of Hydrological Models’ Uncertainty By A Committee Of Machine Learning-Models

This study presents an approach to combine uncertainties of the hydrological model outputs predicted from a number of machine learning models. The machine learning based uncertainty prediction approach is very useful for estimation of hydrological models' uncertainty in particular hydro-metrological situation in real-time application [1]. In this approach the hydrological model realizations from Monte Carlo simulations are used to build different machine learning uncertainty models to predict uncertainty (quantiles of pdf) of the a deterministic output from hydrological model . Uncertainty models are trained using antecedent precipitation and streamflows as inputs. The trained models are then employed to predict the model output uncertainty which is specific for the new input data. We used three machine learning models namely artificial neural networks, model tree, locally weighted regression to predict output uncertainties. These three models produce similar verification results, which can be improved by merging their outputs dynamically. We propose an approach to form a committee of the three models to combine their outputs. The approach is applied to estimate uncertainty of streamflows simulation from a conceptual hydrological model in the Brue catchment in UK and the Bagmati catchment in Nepal. The verification results show that merged output is better than an individual model output. [1] D. L. Shrestha, N. Kayastha, and D. P. Solomatine, and R. Price. Encapsulation of parameteric uncertainty statistics by various predictive machine learning models: MLUE method, Journal of Hydroinformatic, in press, 2013.

NDVI With Artificial Neural Networks For SRTM Elevation Model Improvement – Hydrological Model Application

Digital elevation model (DEM) plays a substantial role in hydrological study, from understanding the catchment characteristics, setting up a hydrological model to mapping the flood risk in the region. Depending on the nature of study and its objectives, high resolution and reliable DEM is often desired to set up a sound hydrological model. However, such source of good DEM is not always available and it is generally high-priced. Obtained through radar based remote sensing, Shuttle Radar Topography Mission (SRTM) is a publicly available DEM with resolution of 92m outside US. It is a great source of DEM where no surveyed DEM is available. However, apart from the coarse resolution, SRTM suffers from inaccuracy especially on area with dense vegetation coverage due to the limitation of radar signals not penetrating through canopy. This will lead to the improper setup of the model as well as the erroneous mapping of flood risk. This paper attempts on improving SRTM dataset, using Normalised Difference Vegetation Index (NDVI), derived from Visible Red and Near Infra-Red band obtained from Landsat with resolution of 30m, and Artificial Neural Networks (ANN). The assessment of the improvement and the applicability of this method in hydrology would be highlighted and discussed.

Spatio-temporal variability behavior of land surface soil water content in shrub- and grass-land

The knowledge of the relationship between spatial variability of the surface soil water content (theta) and its mean across a spatial domain (theta(m)) is crucial for hydrological modeling and understanding soil water dynamics at different scales. With the aim to compare the soil moisture dynamics and variability between the two land uses and to explore the relationship between the spatial variability of theta and theta(m), this study analyzed sets of surface theta measurements performed with an impedance soil moisture probe, collected 136 times during a period of one year in two transects covering different land uses, i.e., korshinsk peashrub transect (KPT) and bunge needlegrass transect (BNT), in a watershed of the Loess Plateau, China. Results showed that the temporal pattern of theta behaved similarly for the two land uses, with both relative wetter soils during wet period and relative drier soils during dry period recognized in BNT. Soil moisture tended to be temporally stable among different dates, and more stable patterns could be observed for dates with more similar soil water conditions. The magnitude of the spatial variation of theta in KPT was greater than that in ENT. For both land uses, the standard deviation (SD) of theta in general increased as theta(m) increased, a behavior that could be well described with a natural logarithmic function. Convex relationship of CV and theta(m) and the maximum CV for both land uses (43.5% in KPT and 41.0% in BNT) can, therefore, be ascertained. Geostatistical analysis showed that the range in KPT (9.1 m) was shorter than that in BNT (15.1 m). The nugget effects, the structured variability, hence the total variability increased as theta(m) increased. For both land uses, the spatial dependency in general increased with increasing theta(m). 2011 Elsevier B.V. All rights reserved.

Previsão de cheias em Barcelos

Dissertação de mestrado integrado em Engenharia Civil

A methodology for the adaptation of a PMP at the determination of a PMF

This paper presents a new type of very fine grid hydrological model based on the spatiotemporal repartition of a PMP (Probable Maximum Precipitation) and on the topography. The goal is to estimate the influence of this rain on a PMF (Probable Maximum Flood) on a catchment area in Switzerland. The spatiotemporal distribution of the PMP was realized using six clouds modeled by the advection-diffusion equation. The equation shows the movement of the clouds over the terrain and also gives the evolution of the rain intensity in time. This hydrological modeling is followed by a hydraulic modeling of the surface and subterranean flow, done considering the factors that contribute to the hydrological cycle, such as the infiltration, the resurgence and the snowmelt. These added factors make the developed model closer to reality and also offer flexibility in the initial condition that is added to the factors concerning the PMP, such as the duration of the rain, the speed and direction of the wind. All these initial conditions taken together offer a complete image of the PMF.

Impacts of deforestation on water balance components of a watershed on the Brazilian East Coast

The Brazilian East coast was intensely affected by deforestation, which drastically cut back the original biome. The possible impacts of this process on water resources are still unknown. The purpose of this study was an evaluation of the impacts of deforestation on the main water balance components of the Galo creek watershed, in the State of Espírito Santo, on the East coast of Brazil. Considering the real conditions of the watershed, the SWAT model was calibrated with data from 1997 to 2000 and validated for the period between 2001 and 2003. The calibration and validation processes were evaluated by the Nash-Sutcliffe efficiency coefficient and by the statistical parameters (determination coefficient, slope coefficient and F test) of the regression model adjusted for estimated and measured flow data. After calibration and validation of the model, new simulations were carried out for three different land use scenarios: a scenario in compliance with the law (C1), assuming the preservation of PPAs (permanent preservation areas); an optimistic scenario (C2), which considers the watershed to be almost entirely covered by native vegetation; and a pessimistic scenario (C3), in which the watershed would be almost entirely covered by pasture. The scenarios C1, C2 and C3 represent a soil cover of native forest of 76, 97 and 0 %, respectively. The results were compared with the simulation, considering the real scenario (C0) with 54 % forest cover. The Nash-Sutcliffe coefficients were 0.65 and 0.70 for calibration and validation, respectively, indicating satisfactory results in the flow simulation. A mean reduction of 10 % of the native forest cover would cause a mean annual increase of approximately 11.5 mm in total runoff at the watershed outlet. Reforestation would ensure minimum flows in the dry period and regulate the maximum flow of the main watercourse of the watershed.

The estimation of PMP and PMF on alpine basins in Switzerland

This paper presents a very fine grid hydrological model based on the spatiotemporal repartition of precipitation and on the topography. The goal is to estimate the flood on a catchment area, using a Probable Maximum Precipitation (PMP) leading to a Probable Maximum Flood (PMF). The spatiotemporal distribution of the precipitation was realized using six clouds modeled by the advection-diffusion equation. The equation shows the movement of the clouds over the terrain and also gives the evolution of the rain intensity in time. This hydrological modeling is followed by a hydraulic modeling of the surface and subterranean flows, done considering the factors that contribute to the hydrological cycle, such as the infiltration, the exfiltration and the snowmelt. This model was applied to several Swiss basins using measured rain, with results showing a good correlation between the simulated and observed flows. This good correlation proves that the model is valid and gives us the confidence that the results can be extrapolated to phenomena of extreme rainfall of PMP type. In this article we present some results obtained using a PMP rainfall and the developed model.

Georeferenced database generation with the purpose of hydrologic molding in reservoirs of the hydrographic basin of Jaguaribe river in the state of Ceará, Brazil

The edafoclimatic conditions of the Brazilian semiarid region favor the water loss by surface runoff. The state of Ceará, almost completely covered by semiarid, has developed public policies for the construction of dams in order to attend the varied water demand. Several hydrological models were developed to support decisive processes in the complex management of reservoirs. This study aimed to establish a methodology for obtaining a georeferenced database suitable for use as input data in hydrological modeling in the semiarid of Ceará. It was used images of Landsat satellite and SRTM Mission, and soil maps of the state of Ceará. The Landsat images allowed the determination of the land cover and the SRTM Mission images, the automatic delineation of hydrographic basins. The soil type was obtained through the soil map. The database was obtained for Jaguaribe River hydrographic basin, in the state of Ceará, and is applicable to hydrological modeling based on the Curve Number method for estimating the surface runoff.

Utilisation du concept de connectivité en hydrologie : définitions, approches expérimentales et éléments de modélisation

Alors que certains mécanismes pourtant jugés cruciaux pour la transformation de la pluie en débit restent peu ou mal compris, le concept de connectivité hydrologique a récemment été proposé pour expliquer pourquoi certains processus sont déclenchés de manière épisodique en fonction des caractéristiques des événements de pluie et de la teneur en eau des sols avant l’événement. L’adoption de ce nouveau concept en hydrologie reste cependant difficile puisqu’il n’y a pas de consensus sur la définition de la connectivité, sa mesure, son intégration dans les modèles hydrologiques et son comportement lors des transferts d’échelles spatiales et temporelles. Le but de ce travail doctoral est donc de préciser la définition, la mesure, l’agrégation et la prédiction des processus liés à la connectivité hydrologique en s’attardant aux questions suivantes : 1) Quel cadre méthodologique adopter pour une étude sur la connectivité hydrologique ?, 2) Comment évaluer le degré de connectivité hydrologique des bassins versants à partir de données de terrain ?, et 3) Dans quelle mesure nos connaissances sur la connectivité hydrologique doivent-elles conduire à la modification des postulats de modélisation hydrologique ? Trois approches d’étude sont différenciées, soit i) une approche de type « boite noire », basée uniquement sur l’exploitation des données de pluie et de débits sans examiner le fonctionnement interne du bassin versant ; ii) une approche de type « boite grise » reposant sur l’étude de données géochimiques ponctuelles illustrant la dynamique interne du bassin versant ; et iii) une approche de type « boite blanche » axée sur l’analyse de patrons spatiaux exhaustifs de la topographie de surface, la topographie de subsurface et l’humidité du sol. Ces trois approches sont ensuite validées expérimentalement dans le bassin versant de l’Hermine (Basses Laurentides, Québec). Quatre types de réponses hydrologiques sont distingués en fonction de leur magnitude et de leur synchronisme, sachant que leur présence relative dépend des conditions antécédentes. Les forts débits enregistrés à l’exutoire du bassin versant sont associés à une contribution accrue de certaines sources de ruissellement, ce qui témoigne d’un lien hydraulique accru et donc d’un fort degré de connectivité hydrologique entre les sources concernées et le cours d’eau. Les aires saturées couvrant des superficies supérieures à 0,85 ha sont jugées critiques pour la genèse de forts débits de crue. La preuve est aussi faite que les propriétés statistiques des patrons d’humidité du sol en milieu forestier tempéré humide sont nettement différentes de celles observées en milieu de prairie tempéré sec, d’où la nécessité d’utiliser des méthodes de calcul différentes pour dériver des métriques spatiales de connectivité dans les deux types de milieux. Enfin, la double existence de sources contributives « linéaires » et « non linéaires » est mise en évidence à l’Hermine. Ces résultats suggèrent la révision de concepts qui sous-tendent l’élaboration et l’exécution des modèles hydrologiques. L’originalité de cette thèse est le fait même de son sujet. En effet, les objectifs de recherche poursuivis sont conformes à la théorie hydrologique renouvelée qui prône l’arrêt des études de particularismes de petite échelle au profit de l’examen des propriétés émergentes des bassins versants telles que la connectivité hydrologique. La contribution majeure de cette thèse consiste ainsi en la proposition d’une définition unifiée de la connectivité, d’un cadre méthodologique, d’approches de mesure sur le terrain, d’outils techniques et de pistes de solution pour la modélisation des systèmes hydrologiques.