Extension And Testing Of A 2D Hydrodynamic Model For Direct Rainfall Runoff Simulation

While the simulation of flood risks originating from the overtopping of river banks is well covered within continuously evaluated programs to improve flood protection measures, flash flooding is not. Flash floods are triggered by short, local thunderstorm cells with high precipitation intensities. Small catchments have short response times and flow paths and convective thunder cells may result in potential flooding of endangered settlements. Assessing local flooding and pathways of flood requires a detailed hydraulic simulation of the surface runoff. Hydrological models usually do not incorporate surface runoff at this detailedness but rather empirical equations are applied for runoff detention. In return 2D hydrodynamic models usually do not allow distributed rainfall as input nor are any types of soil/surface interaction implemented as in hydrological models. Considering several cases of local flash flooding during the last years the issue emerged for practical reasons but as well as research topics to closing the model gap between distributed rainfall and distributed runoff formation. Therefore, a 2D hydrodynamic model, depth-averaged flow equations using the finite volume discretization, was extended to accept direct rainfall enabling to simulate the associated runoff formation. The model itself is used as numerical engine, rainfall is introduced via the modification of waterlevels at fixed time intervals. The paper not only deals with the general application of the software, but intends to test the numerical stability and reliability of simulation results. The performed tests are made using different artificial as well as measured rainfall series as input. Key parameters of the simulation such as losses, roughness or time intervals for water level manipulations are tested regarding their impact on the stability.

Performance Evaluation Of SMOS Soil Moisture Retrieval Parameters For Hydrological Application

Microwave remote sensing has high potential for soil moisture retrieval. However, the efficient retrieval of soil moisture depends on optimally choosing the soil moisture retrieval parameters. In this study first the initial evaluation of SMOS L2 product is performed and then four approaches regarding soil moisture retrieval from SMOS brightness temperature are reported. The radiative transfer equation based tau-omega rationale is used in this study for the soil moisture retrievals. The single channel algorithms (SCA) using H polarisation is implemented with modifications, which includes the effective temperatures simulated from ECMWF (downscaled using WRF-NOAH Land Surface Model (LSM)) and MODIS. The retrieved soil moisture is then utilized for soil moisture deficit (SMD) estimation using empirical relationships with Probability Distributed Model based SMD as a benchmark. The square of correlation during the calibration indicates a value of R2 =0.359 for approach 4 (WRF-NOAH LSM based LST with optimized roughness parameters) followed by the approach 2 (optimized roughness parameters and MODIS based LST) (R2 =0.293), approach 3 (WRF-NOAH LSM based LST with no optimization) (R2 =0.267) and approach 1(MODIS based LST with no optimization) (R2 =0.163). Similarly, during the validation a highest performance is reported by approach 4. The other approaches are also following a similar trend as calibration. All the performances are depicted through Taylor diagram which indicates that the H polarisation using ECMWF based LST is giving a better performance for SMD estimation than the original SMOS L2 products at a catchment scale.

Validation of the Deardorff model for estimating energy balance components for a sugarcane crop

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Short-term temporal changes of bare soil CO2 fluxes after tillage described by first-order decay models

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Caenorhabditis elegans as a model to screen plant extracts and compounds as natural anthelmintics for veterinary use

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Deciphering the weathering processes using environmental mineralogy and geochemistry: Towards an integrated model of laterite and podzol genesis in the Upper Amazon Basin

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Soil loss risk and habitat quality in streams of a meso-scale river basin

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

First-order decay models to describe soil C-CO2 Loss after rotary tillage

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Simulation of within field variability of corn yield with Ceres-Maize model

The CERES-Maize model was used to estimate the spatial variability in corn (Zea mays L.) yield for 1995 and 1996 using data measured on soil profiles located on a 30.5 m grid within a 3.9 ha field in Michigan. The model was calibrated for one grid profile for the 1995 and then used to simulate corn yield for all grid points for the 2 yrs. For the calibration for 1995, the model predicted corn yield within 2%. For 1995, the model predicted yield variability very well (r(2) = 0.85), producing similar yield maps with differences generally within +/- 300 kg ha(-1). For 1996, the model predicted low grain yields (1167 kg ha(-1)) compared with measured (8928 kg ha(-1)) because the model does not account for horizontal water movement within the landscape or water contributions from a water table. Under nonlimiting water conditions, the model performed well (average of 8717 vs. 8948 kg ha(-1)) but under-estimated the measured yield variability.

Modelling short-term temporal changes of bare soil CO2 emissions in a tropical agrosystem by using meteorological data

Determining the variability of carbon dioxide emission from soils is an important task as soils are among the largest sources of carbon in biosphere. In this work the temporal variability of bare soil CO2 emissions was measured over a 3-week period. Temporal changes in soil CO2 emission were modelled in terms of the changes that occurred in solar radiation (SR), air temperature (T-air), air humidity (AR), evaporation (EVAP) and atmospheric pressure (ATM) registered during the time period that the experiment was conducted. The multiple regression analysis (backward elimination procedure) includes almost all the meteorological variables and their interactions into the final model (R-2 = 0.98), but solar radiation showed to be the one of the most relevant variables. The present study indicates that meteorological data could be taken into account as the main forces driving the temporal variability of carbon dioxide emission from bare soils, where microbial activity is the sole source of carbon dioxide emitted. (C) 2003 Elsevier B.V. All rights reserved.

Prediction and spatial variability of soil dynamic properties in sugar cane fields of São Paulo State Brazil

The objective of this work was to model and diagnose the spatial variability of soil load support capacity (SLSC) in sugar cane crop fields, as well as to evaluate the management impact on São Paulo State soil structure. The investigated variables were: pressure preconsolidation (sigma(p)), apparent cohesion () and internal friction angle (). The conclusions from the results were that the models and spatial dependence maps constitute important tools in the prediction and location of the mechanical internal strength of soils cultivated with sugar cane. They will help future soil management decisions so that soil structure sustainability will not be compromised.

Model approach for estimating potato pesticide bioconcentration factor

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Spatial and temporal variability in soil CO2-C emissions and relation to soil temperature at King George Island, maritime Antarctica

Few studies have examined the effects of temperature on spatial and temporal trends in soil CO2-C emissions in Antarctica. In this work, we present in situ measurements of CO2-C emissions and assess their relation with soil temperature, using dynamic chambers. We found an exponential relation between CO2 emissions and soil temperature, with the value of Q10 being close to 2.1. Mean emission rates were as low as 0.026 and 0.072 g of CO2-C m-2 h-1 for bare soil and soil covered with moss, respectively, and as high as 0.162 g of CO2-C m-2 h-1 for soil covered with grass, Deschampsia antarctica Desv. (Poaceae). A spatial variability analysis conducted using a 60-point grid, for an area with mosses (Sannionia uncianata) and D. antarctica, yielded a spherical semivariogram model for CO2-C emissions with a range of 1 m. The results suggest that soil temperature is a controlling factor on temporal variations in soil CO2-C emissions, although spatial variations appear to be more strongly related to the distribution of vegetation types. © 2010 Elsevier B.V. and NIPR.

Delineation of specific management areas for coffee cultivation based on the soil-relief relationship and numerical classification

Predicting and mapping productivity areas allows crop producers to improve their planning of agricultural activities. The primary aims of this work were the identification and mapping of specific management areas allowing coffee bean quality to be predicted from soil attributes and their relationships to relief. The study area was located in the Southeast of the Minas Gerais state, Brazil. A grid containing a total of 145 uniformly spaced nodes 50 m apart was established over an area of 31. 7 ha from which samples were collected at depths of 0. 00-0. 20 m in order to determine physical and chemical attributes of the soil. These data were analysed in conjunction with plant attributes including production, proportion of beans retained by different sieves and drink quality. The results of principal component analysis (PCA) in combination with geostatistical data showed the attributes clay content and available iron to be the best choices for identifying four crop production environments. Environment A, which exhibited high clay and available iron contents, and low pH and base saturation, was that providing the highest yield (30. 4l ha-1) and best coffee beverage quality (61 sacks ha-1). Based on the results, we believe that multivariate analysis, geostatistics and the soil-relief relationships contained in the digital elevation model (DEM) can be effectively used in combination for the hybrid mapping of areas of varying suitability for coffee production. © 2012 Springer Science+Business Media New York.

Soil erodibility assessment in a pasture and forest remnant using the inderbitzen device

Brazil has the largest cattle herd in the world with approximately 200 million head. An important feature of the Brazilian cattle industry is that most of its herd is raised on pasture, which constitutes one of the most economical and practical ways to produce and provide food for cattle. However, this production model is mishandled and can lead to soil degradation. Maintaining soil quality is essential for the conservation of natural ecosystems and the areas of production, thus soil quality improves the conditions for biogeochemical cycles. In this context, the objective of this study was to develop a device for testing the Inderbitzen way of assessing soil erodibility in two situations of usage and occupation. Therefore, one area was used as a sample collection occupied by grazing and the other as a forest fragment; both located in the city of Sorocaba in Sao Paulo State, Brazil. Thus, we concluded that the proposed device - the Inderbitzen - proved capable of assessing soil erodibility of the pasture and remnant forest. Accordingly, there was a tendency for a smaller loss of forest soils in the remnant when compared to the degraded pasture. The greatest resistance of the soil erosion in the forest remnant may be associated with the amount of organic matter released by the forest litter in all its diversity, influencing the quality of the structure of aggregates. © 2013 WIT Press.