Hydrological modeling, like runoff modelling for flood prevention, is based on digital elevation models (DEMs). The fact that the DEMs do not represent existing road culverts can lead to considerable hydrological misinterpretations. In order to overcome this limitation, a GIS method was developed to automatically adjust the elevation model, hydrologically enforcing the DEM, so that the results of hydrological modeling accounts for flow through culverts. The hydro-enforced DEM showed to better represent the drainage network than the former DEM when compared with the river map. The topographic wetness index is the most commonly applied topographic index and a good indicator of soil moisture distribution. It has been integrated into many hydrological models and pollution risk indices as well as into the prediction of wetland distribution. Using the hydro-DEM from the previous step and the soil map in conjunction with the TWI, an improved TWI was achieved, namely a soil-topographic wetness index (STI). The linkages between specific soil types and TWI or STI values were analyzed. They revealed a clear linkage between STI values and soil type based on the soil transmissivity (R2=0.77). However, the TWI values showed low correlations to the soil types (R2=0.02). As a specific application, both TWI and STI were tested for the detection of wetlands. Wetlands are important ecosystems which act as buffer zones by filtering pollutants and slowing floodwater. Being able to identify their distribution is important in landscape planning and ecology. A wetland threshold value was determined for each index and their results where compared with the wetland map from the property map (assumed as ground truth) and with the potential wetland area. Finally, a visual validation was performed with the use of an aerial photography. The results showed that the STI performed slightly better than the TWI for the detection of wetlands, detecting 3% more wetlands. The impact of the soil map on the topographic wetness index was therefore determined as positive.

Alluvial groundwater systems are an important source of water for communities and biodiverse riparian corridors throughout the arid and semi-arid Basin and Range Geological Province of western North America. These aquifers and their attendant desert streams have been depleted to support a growing population, while projected climate change could lead to more extreme episodes of drought and precipitation in the future. The only source of replenishment to these aquifers is recharge. This dissertation builds upon previous work to characterize and quantify recharge in arid and semi-arid basins by characterizing the intra-annual seasonality of recharge across the Basin and Range Province, and considering how climate change might impact recharge seasonality and volume, as well as fragile riparian corridors that depend on these hydrologic processes. First, the seasonality of recharge in a basin in the sparsely-studied southern extent of the Basin and Range Province is determined using stable water isotopes of seasonal precipitation and groundwater, and geochemical signatures of groundwater and surface water. In northwestern Mexico in the southern reaches of the Basin and Range, recharge is dominated by winter precipitation (69% ± 42%) and occurs primarily in the uplands. Second, isotopically-based estimates of seasonal recharge fractions in basins across the region are compared to identify patterns in recharge seasonality, and used to evaluate a simple water budget-based model for estimating recharge seasonality, the normalized seasonal wetness index (NSWI). Winter precipitation makes up the majority of annual recharge throughout the region, and North American Monsoon (NAM) precipitation has a disproportionately weak impact on recharge. The NSWI does well in estimating recharge seasonality for basins in the northern Basin and Range, but less so in basins that experience NAM precipitation. Third, the seasonal variation in riparian and non-riparian vegetation greenness, represented by the normalized difference vegetation index (NDVI), is characterized in several of the study basins and climatic and hydrologic controls are identified. Temperature was the most significant driver of vegetation greenness, but precipitation and recharge seasonality played a significant role in some basins at some elevations. Major contributions of this work include a better understanding of recharge in a monsoon-dominated basin, the characterization of recharge seasonality at a regional scale, evaluation of an estimation method for recharge seasonality, and an interpretation of the interaction of seasonal hydrologic processes, vegetation dynamics, and climate change.

Made available in DSpace on 2014-06-11T19:31:34Z (GMT). No. of bitstreams: 0 Previous issue date: 2006-12-11Bitstream added on 2014-06-13T20:42:01Z : No. of bitstreams: 1 mathias_im_dr_botfca.pdf: 1186171 bytes, checksum: a99a3192900af068caf82ad18c373cfa (MD5) / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / Universidade Estadual Paulista (UNESP) / O trabalho descrito nesta tese apresenta o desenvolvimento de um sistema computacional denominado PMNeural, baseado em Redes Neurais Artificiais (RNAs). A finalidade do sistema é o tratamento de dados climáticos e de molhamento foliar por orvalho, visando reconhecer padrões de comportamento de variáveis meteorológicas em relação ao molhamento foliar por orvalho. Para determinar as melhores arquiteturas e algoritmos de treinamento de RNAs, bem como, definir quais as variáveis climáticas que influenciam significativamente na ocorrência do molhamento foliar, foram utilizados dois simuladores: o simulador SNNS (Stuttgart Neural Network Simulator) versão 4.2, que utiliza plataforma operacional Linux e o simulador JavaNNS - Java Neural Network Simulator 1.1, com ambiente de execução Windows, o qual é baseado no SNNS. Foram utilizados dados climáticos de três estudos de caso, dois destes referentes à cultura do trigo, oriundos de locais e datas diferentes. Base de Dados 1 - Fazenda Capão do Cipó, em Castro - PR, safra de inverno de 2003. Base de Dados 2 - Campo Demonstrativo e Experimental da Fundação ABC - Fazenda Palmeirinha, em Piraí do Sul - PR., safra de inverno de 2005. Base de Dados 3 - Posto Agrometeorológico ESALQ/USP em Piracicaba - SP, período entre julho e setembro de 2005. Um quarto estudo de caso foi elaborado a partir dos arquivos dos estudos de casos 1, 2 e 3, utilizando-se as variáveis climáticas comuns, juntamente com seus respectivos índices de molhamento. Dentre os algoritmos de treinamento testados nos simuladores, o Resilient 2 Propagation (Rprop) foi o que apresentou as menores taxas de erro em relação aos outros... / The work described in this thesis presents the development of a computational system named PMNeural based on Artificial Neural Networks (ANNs). The system has for purpose the handle of climatic and leaf wetness data, aiming to recognize patterns of behavior of meteorological variables in relation to the wetness from dew. Two simulators were used in order to determine the best architecture and ANNs training algorithms, as well as, to define which the climatic variables that influence significantly in the leaf wetness occurrence: the SNNS (Stuttgart Neural Network Simulator) version 4.2 for Linux platform, and the JavaNNS - Java Neural Network Simulator 1.1, for Windows platform, which is based on the SNNS. Climatic data of three case studies were used, two related to wheat culture, obtained from different places and dates. Dataset 1 - Capão do Cipó Farm, in Castro - PR, 2003. Dataset 2 - Palmeirinha Farm in Piraí do Sul - PR, 2005 winter crop. Dataset 3 - Meteorological Station of ESALQ/USP in Piracicaba - SP, from July to September, 2005. A fourth case study was elaborated from datasets of the case studies 1, 2 and 3, using the common climatic variables together with their respective wetness indexes. After testing the training algorithms in the simulators, the Resilient Propagation (Rprop) presented lower training errors than the others evaluated methods: Backpropagation Standard, Backpropagation for batch training, Backpropagation with momentum term, Backpropagation with chunkwise update, Backpropagation with Weight Decay and Quickprop. It was verified 4 also that, among the climatic variables used for classification of leaf wetness from dew, the inclusion of the schedule had influenced in the obtaining better ANNs results... (Complete abstract, click electronic access below)

This Thesis presents a framework for modelling species-specific site quality index (SQI) at a spatial resolution of 250 m by integrating biophysical variables of growing degree days (GDD), soil water content (SWC), and incident photosynthetically active radiation (PAR) in descriptions of potential tree growth. Development of GDD maps is based on processing and blending remotely-sensed data acquired with the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor on the Terra satellite and ETM+ sensor on Landsat-7 satellite at spatial resolutions of 250 m and 28.5 m. Descriptions of SWC are based on a temperature-vegetation wetness index (TVWI) that relies on MODIS-based optical and thermal image products. PAR is estimated with an existing solar-radiation distribution model. SQI is defined as a function of species vital attributes and species environmental response to GDD, TVWI, and PAR. The methods are applied to a balsam fir [bF; Abies balsamea (L.) Mill.] dominated region in northwest New Brunswick. Comparisons between SQI and field-based estimates of site index and enhanced vegetation index showed that about 66 and 88% of the values corresponding to a series of Forest Development Survey lines (691 in total) were within 16% of SQI values. On average 92.1% of high bF-content stands (> 50% composition) in the area fell on medium-to-very high SQI values (> 0.50). Based on these agreements, SQI can be perceived as a good predictor of potential tree-species growth in the selection of optimal sites for biomass and wood fibre production.

Submitted by Rafael Marini Paschoaletti Perri dos Santos (rafaelmpps@hotmail.com) on 2017-10-30T19:28:34Z No. of bitstreams: 2 PPGAA_ Dissertação_Rafael Marini PP Santos_2017 (1).pdf: 3014297 bytes, checksum: f71dea6e56def749b21f955b1a8a1ad5 (MD5) Encaminhamento_Dissertação_Rafael Marini dos Santos_PPGAA.pdf: 792545 bytes, checksum: eec6f1001daf58a9614a859a1d455837 (MD5) / Approved for entry into archive by Alini Demarchi (alini@cca.ufscar.br) on 2017-11-30T16:55:11Z (GMT) No. of bitstreams: 2 PPGAA_ Dissertação_Rafael Marini PP Santos_2017 (1).pdf: 3014297 bytes, checksum: f71dea6e56def749b21f955b1a8a1ad5 (MD5) Encaminhamento_Dissertação_Rafael Marini dos Santos_PPGAA.pdf: 792545 bytes, checksum: eec6f1001daf58a9614a859a1d455837 (MD5) / Approved for entry into archive by Alini Demarchi (ri.bar@ufscar.br) on 2018-01-15T18:25:58Z (GMT) No. of bitstreams: 2 PPGAA_ Dissertação_Rafael Marini PP Santos_2017 (1).pdf: 3014297 bytes, checksum: f71dea6e56def749b21f955b1a8a1ad5 (MD5) Encaminhamento_Dissertação_Rafael Marini dos Santos_PPGAA.pdf: 792545 bytes, checksum: eec6f1001daf58a9614a859a1d455837 (MD5) / Made available in DSpace on 2018-02-01T13:31:38Z (GMT). No. of bitstreams: 2 PPGAA_ Dissertação_Rafael Marini PP Santos_2017 (1).pdf: 3014297 bytes, checksum: f71dea6e56def749b21f955b1a8a1ad5 (MD5) Encaminhamento_Dissertação_Rafael Marini dos Santos_PPGAA.pdf: 792545 bytes, checksum: eec6f1001daf58a9614a859a1d455837 (MD5) Previous issue date: 2017-06-27 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / Nowadays, society has a challenge to deal with sustainable water use. High demand and water contamination, environmental degradation and the unpredictability of climate changes are some water insecurity causes. Riparian forests maintenance offers water ecosystems services, but in some cases the riparian ecosystem is in a degraded condition that require human intervention actions for forest restoration. In this way, geotechnologies help us to infer about physical landscape characteristics where watershed is a basic unity for environmental planning. This study aimed to identify important hydrologically areas of Consulta stream watershed and Retiro stream watershed and propose priorities areas for forest restoration and sustainable agricultural destination. The two watersheds are the main sources of public water supply in the city of Bebedouro (Brazil). It is hypothesized that the limits established by Brazilian forest law (BFL) riparian buffers zones may not fully guarantee the two watersheds riparian areas protection. It was assumed that the forest community plays an important role in the attenuation of chemical elements and sediments, and that is essential that there is a disruption of potentially polluting activities near riparian areas. It was used in the study images from orbital sensors spatial resolution 30 m and 90 m and topographical map 1:50.000 for obtaining and processing elevations data and land use in geographic information system (GIS), and environmental legislation. The results allowed to characterize the watersheds that are surrounding and presented similarities in their physical parameters (basin form, drainage density, channel length, and others) and the Topographic Wetness Index (TWI) class distribution, slope class, landscape elements and land use. Three scenarios of priority areas for forest restoration were generated. It was observed that the priority areas are distributed close to the drainage channel of watersheds and are partially related to required areas by BFL. It can be concluded that in the three scenarios established the BFL may not be sufficient for the full protection of riparian sites and the adopted methodology proved to be efficient for guiding water resources management actions at larges scales. / Resolver conflitos relacionados ao uso da água é um desafio para a sociedade atual. Dentre os fatores que preocupam a segurança hídrica destacam-se a crescente demanda de consumo, a contaminação dos mananciais, a degradação de áreas naturais e a imprevisibilidade das mudanças climáticas que resultam em períodos irregulares de secas e estiagens. As matas ripárias oferecem funções importantes para os serviços ecossistêmicos de provisão hídrica, mas em algumas regiões encontram-se degradadas e com baixa resiliência, necessitando de ações de restauração florestal. As geotecnologias permitem inferir as características físicas da paisagem e a microbacia hidrográfica (MBH) é uma unidade básica para o planejamento ambiental. Este trabalho teve por objetivo identificar áreas hidrologicamente importantes nas MBHs do Córrego da Consulta e do Córrego do Retiro, de abastecimento público do município de Bebedouro (SP), e propor áreas prioritárias para a restauração florestal e manejo diferenciado. A hipótese é que as áreas de preservação permanente (APPs) de 30 m não são suficientes para abranger por completo as áreas ripárias destas MBHs. Considerou-se a eficiência da comunidade florestal em atenuar agentes químicos, sedimentos e a necessidade de interrupção de atividades potencialmente poluidoras próximas às áreas ripárias. Foram utilizadas imagens orbitais com resoluções espaciais de 30 m e 90 m, carta topográfica em escala 1:50.000 para obtenção e processamento de dados de elevação e uso e ocupação dos solos em sistema de informações geográficas (SIG), e legislação ambiental pertinente. Os resultados permitiram caracterizar as duas MBHs que são circunvizinhas e apresentaram semelhanças nos seus parâmetros físicos (fator de forma de bacia, densidade de drenagem, comprimento de canais, entre outros), na distribuição das classes do índice topográfico de umidade (ITU), de classes de declividade, de elementos de paisagem e de uso e ocupação dos solos. Foram gerados três cenários de áreas prioritárias para a restauração florestal. Observou-se que as áreas prioritárias para a restauração florestal e manejo diferenciado estão distribuídas próximas ao canal de drenagem das MBHs e estão relacionadas às APPs. Conclui-se que, nos três cenários estabelecidos, as APPs não são suficientes para a integral proteção de locais de caráter ripário e a metodologia adotada se mostrou eficiente para apontar ações de gestão de recursos hídricos em escalas maiores.

Resumo: O trabalho descrito nesta tese apresenta o desenvolvimento de um sistema computacional denominado PMNeural, baseado em Redes Neurais Artificiais (RNAs). A finalidade do sistema é o tratamento de dados climáticos e de molhamento foliar por orvalho, visando reconhecer padrões de comportamento de variáveis meteorológicas em relação ao molhamento foliar por orvalho. Para determinar as melhores arquiteturas e algoritmos de treinamento de RNAs, bem como, definir quais as variáveis climáticas que influenciam significativamente na ocorrência do molhamento foliar, foram utilizados dois simuladores: o simulador SNNS (Stuttgart Neural Network Simulator) versão 4.2, que utiliza plataforma operacional Linux e o simulador JavaNNS - Java Neural Network Simulator 1.1, com ambiente de execução Windows, o qual é baseado no SNNS. Foram utilizados dados climáticos de três estudos de caso, dois destes referentes à cultura do trigo, oriundos de locais e datas diferentes. Base de Dados 1 - Fazenda Capão do Cipó, em Castro - PR, safra de inverno de 2003. Base de Dados 2 - Campo Demonstrativo e Experimental da Fundação ABC - Fazenda Palmeirinha, em Piraí do Sul - PR., safra de inverno de 2005. Base de Dados 3 - Posto Agrometeorológico ESALQ/USP em Piracicaba - SP, período entre julho e setembro de 2005. Um quarto estudo de caso foi elaborado a partir dos arquivos dos estudos de casos 1, 2 e 3, utilizando-se as variáveis climáticas comuns, juntamente com seus respectivos índices de molhamento. Dentre os algoritmos de treinamento testados nos simuladores, o Resilient 2 Propagation (Rprop) foi o que apresentou as menores taxas de erro em relação aos outros... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: The work described in this thesis presents the development of a computational system named PMNeural based on Artificial Neural Networks (ANNs). The system has for purpose the handle of climatic and leaf wetness data, aiming to recognize patterns of behavior of meteorological variables in relation to the wetness from dew. Two simulators were used in order to determine the best architecture and ANNs training algorithms, as well as, to define which the climatic variables that influence significantly in the leaf wetness occurrence: the SNNS (Stuttgart Neural Network Simulator) version 4.2 for Linux platform, and the JavaNNS - Java Neural Network Simulator 1.1, for Windows platform, which is based on the SNNS. Climatic data of three case studies were used, two related to wheat culture, obtained from different places and dates. Dataset 1 - Capão do Cipó Farm, in Castro - PR, 2003. Dataset 2 - Palmeirinha Farm in Piraí do Sul - PR, 2005 winter crop. Dataset 3 - Meteorological Station of ESALQ/USP in Piracicaba - SP, from July to September, 2005. A fourth case study was elaborated from datasets of the case studies 1, 2 and 3, using the common climatic variables together with their respective wetness indexes. After testing the training algorithms in the simulators, the Resilient Propagation (Rprop) presented lower training errors than the others evaluated methods: Backpropagation Standard, Backpropagation for batch training, Backpropagation with momentum term, Backpropagation with chunkwise update, Backpropagation with Weight Decay and Quickprop. It was verified 4 also that, among the climatic variables used for classification of leaf wetness from dew, the inclusion of the schedule had influenced in the obtaining better ANNs results... (Complete abstract, click electronic access below) / Orientador: Angelo Cataneo / Coorientador: Alaine Margarete Guimarães / Banca: Célia Regina Lopes Zimback / Banca: Marco Antonio Martim Biaggioni / Banca: Manoel Henrique Salgado / Banca: Marcelo Giovanetti Canteri / Doutor

<p>The main objectives of this thesis are to study if a topographic wetness index (TWI) could be used as a tool for predicting the spatial distribution of vascular plant species richness in the boreal forest as well as to study congruence in species richness between vascular plants, liverworts, mosses and lichens. A wetness index ln(a/tanβ) based on topography was used to assign a specific TWI-value to every 20 x 20m grid in two 25 km2 boreal forest landscapes (differing in average soil pH) in northern Sweden. Soil pH is known to be influenced by groundwater and to affect plant species richness in other biomes. Therefore, the relationships between plant species richness, TWI and soil pH were also studied. </p><p>The results showed that the majority of the investigated boreal forest landscapes were relatively dry and species-poor, whereas interspersed patches linked to areas with relatively high TWI had species-rich vegetation including the species of the drier parts of the landscape. There was a positive relationship between species richness of vascular plants and the TWI in both landscapes, but varied with average soil pH. TWI explained 30 % and 52 % of the variation in plant species richness in the landscape with lower and higher pH, respectively. The proportion of regionally uncommon plants also increased with TWI. Testing different calculation methods of the TWI resulted in a large variation in correlation strengths between the various TWI-values and different measured variables (species richness of vascular plants, soil pH, groundwater flow and soil moisture). The relationship between plant species richness and TWI could be further improved with some of the calculation methods. </p><p>When studying correlations in species richness using data sets from boreal forest in northern Sweden, strong positive correlations among vascular plants, mosses and liverworts were found, but no significant correlation between macrolichens and any of the other groups. This result could be explained by that the species number of each of the three related groups increases with ambient moisture, whereas the species number of macrolichens is weakly associated with moisture. </p><p>In conclusion, the TWI could become a useful tool in conservation management for identifying areas of special interest prior to field inventories. Since vascular plants can be used as an indicator taxon for species richness of mosses and liverworts, high TWI-values indicate areas of species hotspots of these taxa.</p> / <p>Syftet med avhandlingen är att dels studera om ett topografiskt fuktighetsindex skulle kunna vara användbart för att förutsäga fördelningen av kärlväxters artrikedom i boreal skog, dels att studera om den rumsliga fördelningen av artrikedom hos kärlväxter, blad- och levermossor samt lavar sammanfaller.</p><p>Ett fuktighetsindex, ln(a/tanβ), som bara är baserat på topografi användes för att beräkna ett indexvärde för varje 20 x 20 m grid i två 25 km2 stora boreala skogslandskap (med i medeltal olika mark-pH) i norra Sverige. Det är känt att mark-pH påverkas av grundvatten och att pH i sin tur påverkar artrikedom hos kärlväxter i andra biom. Därför studerades även sambanden mellan kärlväxters artrikedom, mark pH och TWI.</p><p>Resultaten visade att större delen av det studerade boreala landskapet var relativt torrt och artfattigt, medan mindre utspridda områden med höga TWI-värden var artrika på kärlväxter och här växte även arter som återfanns i de torra delarna av skogen. Sambandet mellan artrikedom hos kärlväxter och TWI var positivt i båda landskapen, men påverkades av de olika nivåerna på mark-pH. TWI förklarade 30 % av variationen i artrikedom i området med lägre mark-pH respektive 50 % i området med högre mark-pH. Andelen kärlväxter som klassificeras som icke vanliga i respektive region ökade också med TWI. Med andra beräkningsmetoder för TWI visade det sig att styrkan på korrelationerna mellan TWI och olika uppmätta variabler (artrikedom hos kärlväxter, mark-pH, grundvattennivå och markfuktighet) varierade mycket. Sambandet mellan artrikedom hos kärlväxter och TWI kunde förbättras ytterligare med vissa beräkningsmetoder.</p><p>Då korrelationer i artrikedom studerades användes ett dataset från boreal skog i norra Sverige. Resultaten visade på starka, positiva korrelationer mellan kärlväxter, blad- och levermossor, men inga korrelationer mellan någon av dessa grupper och lavar. Detta kunde förklaras med att artrikedom hos de tre korrelerande organismgrupperna ökar med ökad fuktighet, medan artrikedom hos lavar inte är kopplat till fukt.</p><p>Huvudslutsatsen i avhandlingen är att TWI, som endast är baserad på topograpfiskt data, skulle kunna bli ett värdefullt redskap i naturvårdsplanering för att identifiera särskilt intressanta skogsområden innan man gör fältinventeringar. Eftersom studien visar att kärlväxter kan användas som en indikator grupp för artrikedom hos blad- och levermossor indikerar höga TWI-värden områden med hög artrikedom även vad gäller dessa taxa.</p>

The main objectives of this thesis are to study if a topographic wetness index (TWI) could be used as a tool for predicting the spatial distribution of vascular plant species richness in the boreal forest as well as to study congruence in species richness between vascular plants, liverworts, mosses and lichens. A wetness index ln(a/tanβ) based on topography was used to assign a specific TWI-value to every 20 x 20m grid in two 25 km2 boreal forest landscapes (differing in average soil pH) in northern Sweden. Soil pH is known to be influenced by groundwater and to affect plant species richness in other biomes. Therefore, the relationships between plant species richness, TWI and soil pH were also studied. The results showed that the majority of the investigated boreal forest landscapes were relatively dry and species-poor, whereas interspersed patches linked to areas with relatively high TWI had species-rich vegetation including the species of the drier parts of the landscape. There was a positive relationship between species richness of vascular plants and the TWI in both landscapes, but varied with average soil pH. TWI explained 30 % and 52 % of the variation in plant species richness in the landscape with lower and higher pH, respectively. The proportion of regionally uncommon plants also increased with TWI. Testing different calculation methods of the TWI resulted in a large variation in correlation strengths between the various TWI-values and different measured variables (species richness of vascular plants, soil pH, groundwater flow and soil moisture). The relationship between plant species richness and TWI could be further improved with some of the calculation methods. When studying correlations in species richness using data sets from boreal forest in northern Sweden, strong positive correlations among vascular plants, mosses and liverworts were found, but no significant correlation between macrolichens and any of the other groups. This result could be explained by that the species number of each of the three related groups increases with ambient moisture, whereas the species number of macrolichens is weakly associated with moisture. In conclusion, the TWI could become a useful tool in conservation management for identifying areas of special interest prior to field inventories. Since vascular plants can be used as an indicator taxon for species richness of mosses and liverworts, high TWI-values indicate areas of species hotspots of these taxa. / Syftet med avhandlingen är att dels studera om ett topografiskt fuktighetsindex skulle kunna vara användbart för att förutsäga fördelningen av kärlväxters artrikedom i boreal skog, dels att studera om den rumsliga fördelningen av artrikedom hos kärlväxter, blad- och levermossor samt lavar sammanfaller. Ett fuktighetsindex, ln(a/tanβ), som bara är baserat på topografi användes för att beräkna ett indexvärde för varje 20 x 20 m grid i två 25 km2 stora boreala skogslandskap (med i medeltal olika mark-pH) i norra Sverige. Det är känt att mark-pH påverkas av grundvatten och att pH i sin tur påverkar artrikedom hos kärlväxter i andra biom. Därför studerades även sambanden mellan kärlväxters artrikedom, mark pH och TWI. Resultaten visade att större delen av det studerade boreala landskapet var relativt torrt och artfattigt, medan mindre utspridda områden med höga TWI-värden var artrika på kärlväxter och här växte även arter som återfanns i de torra delarna av skogen. Sambandet mellan artrikedom hos kärlväxter och TWI var positivt i båda landskapen, men påverkades av de olika nivåerna på mark-pH. TWI förklarade 30 % av variationen i artrikedom i området med lägre mark-pH respektive 50 % i området med högre mark-pH. Andelen kärlväxter som klassificeras som icke vanliga i respektive region ökade också med TWI. Med andra beräkningsmetoder för TWI visade det sig att styrkan på korrelationerna mellan TWI och olika uppmätta variabler (artrikedom hos kärlväxter, mark-pH, grundvattennivå och markfuktighet) varierade mycket. Sambandet mellan artrikedom hos kärlväxter och TWI kunde förbättras ytterligare med vissa beräkningsmetoder. Då korrelationer i artrikedom studerades användes ett dataset från boreal skog i norra Sverige. Resultaten visade på starka, positiva korrelationer mellan kärlväxter, blad- och levermossor, men inga korrelationer mellan någon av dessa grupper och lavar. Detta kunde förklaras med att artrikedom hos de tre korrelerande organismgrupperna ökar med ökad fuktighet, medan artrikedom hos lavar inte är kopplat till fukt. Huvudslutsatsen i avhandlingen är att TWI, som endast är baserad på topograpfiskt data, skulle kunna bli ett värdefullt redskap i naturvårdsplanering för att identifiera särskilt intressanta skogsområden innan man gör fältinventeringar. Eftersom studien visar att kärlväxter kan användas som en indikator grupp för artrikedom hos blad- och levermossor indikerar höga TWI-värden områden med hög artrikedom även vad gäller dessa taxa.

In boreal catchments, stream water chemistry is influenced and controlled by several landscape factors. The influence of spatially distributed variables is in turn dependent on the hydrological scale. Headwater streams have larger variability of water chemistry, and thus together represent a large biodiversity, and therefore need to be monitored in official environmental assessments. One objective of this study was, using Geographical Information Systems (GIS), to analyse co-variation between landscape variables and water chemistry and to determine which of the landscape variables have a major influence on the concentration of dissolved organic carbon (DOC) in headwater streams. Another objective was to find a simple method for predicting sources of DOC, using official map data and publically available GIS applications. Totally 85 headwater catchments (0.1-4 km2) in the county of Värmland, western south Sweden, were used in the study. Water chemistry was analysed for water sampled at low, medium and high flows, and landscape variables were extracted from official map data sources: topographic maps, a digital elevation model (DEM, 50 m grid), and vegetation data. Statistical analyses showed that topography (mean slope and mean topographic wetness index (TWI)) and wetland cover often correlated well with DOC in headwater catchments. Official map data could satisfactorily extract landscape variables (mean slope, mean TWI) that were useful in predicting stream water chemistry (DOC). A high-resolution elevation model, which was generated by interpolation of photogrammetric data, was used to calculate and evaluate two different wetness indices and their ability to predict the occurrence of wetlands in six catchments of different sizes and topography. The SAGA (System for Automated Geoscientific Analyses) wetness index (SWI) gave substantially better results than the TWI. The effects of resolution of DEMs on calculations of the SWI were investigated using 5, 10, 25 and 50 m grids. The results showed that SWI values increased with increasing cell size. The near linear increment of mean values for resolutions 10-50 m suggests a independence of terrain type and catchment size, which supported previous findings that indicated that mean slope and mean wetness index calculated from coarse elevation models may be used for prediction of DOC in headwater streams.

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Social demands on soil information have grown dramatically, meanwhile the soil surveys are seldom carried out in the country. Digital soil mapping techniques can be applied to infer the spatial distribution of soil from existing soil maps or from reference areas, extrapolating this information to areas not mapped. The purpose of this study was to apply in a Geographic Information System the Multiple Logistic Regressions (MLR) using Principal Components (PC) as explanatory variables to predict soil classes spatial distribution. The study area was the region of municipality São Pedro do Sul / RS. For the development of predictive models a set of nine terrain attributes were used. Model training was executed on an existing soil map and with a survey carried out in a reference area, both in a 1:50.000 scale. The first three retained PC explained 65.57% of the data variability. The predictive models which used PC had lower values of kappa index. The most accurate predicted map reached a kappa value of 63.20% and was generated by using the nine attributes of land as predictive covariates. The mapping accuracy is sensitive to similarities between the mapped classes, and mapping in a more homogeneous categorical level reduces the accuracy of the predicted maps. Soil classes relatively not representative in the training maps are not properly spatialized. The use of MLR allows spatializing of soil classes to areas not mapped, although the use of PC needs to be tested with a larger number of covariates. / As demandas da sociedade pela informação solo têm crescido, porém levantamentos pedológicos praticamente não ocorrem mais no país. Técnicas de Mapeamento Digital do Solo podem ser empregadas para inferir a distribuição espacial de classes de solos a partir de mapas existentes e áreas de referência, extrapolando esta informação para áreas não mapeadas. O objetivo deste estudo foi empregar em um Sistema de Informações Geográficas as Regressões Logísticas Múltiplas (RLM) utilizando-se de Componentes Principais (CP) como variáveis explicativas para a predição espacial de classes de solos. A área de estudo foi na região do município de São Pedro do Sul / RS. Para o desenvolvimento dos modelos preditivos foram utilizados um conjunto de nove atributos do terreno. O treinamento dos modelos foi executado em um mapa de solos existente, e em um levantamento realizado em áreas de referência, ambos na escala 1:50.000. As três primeiras CP retidas explicaram 65,57% da variabilidade dos dados. Os modelos preditivos que empregaram CP obtiveram menores valores do índice kappa. O mapa predito mais acurado empregou os nove atributos do terreno e alcançou um valor de kappa de 63,20%. A acurácia do mapeamento é sensível a semelhança entre as classes mapeadas, e o mapeamento em níveis categóricos mais homogêneos reduz a precisão dos mapas preditos. Classes de solos relativamente pouco representativas não são corretamente espacializadas. O emprego de RLM permite espacializar classes de solos para áreas não mapeadas, embora o emprego de CP necessite ser testado com um maior número de covariáveis.