Accurate hydrological modelling to evaluate the impacts of climate and land use change on water resources is pivotal to sustainable management. Soil information is an important input in hydrological models but is often not available at adequate scale with appropriate attributes for direct parameterisation of the models. In this study, conducted in three quaternary catchments in the midlands of KwaZulu-Natal, three different soil information sets were used to configure SWAT+, a revised version of the Soil and Water Assessment Tool (SWAT). The datasets were: (i) the Land Type database (currently the only soil dataset covering the whole of South Africa), (ii) disaggregation of the Land Type database using digital soil mapping techniques (called DSMART), and (iii) a dataset where DSMART were complemented by field observations and interpretations of the hydropedological behaviour of the soils (DSMART+). Simulated streamflow was compared with measured streamflow at three weirs with long-term measurements, and the impact of the soil datasets on water balance simulations was evaluated. In general, the simulations were acceptable when compared to other studies, but could be improved through calibration and including small reservoirs in the model. The DSMART+ dataset yielded more accurate simulations of streamflow in all three catchments with Nash-Sutcliffe efficiencies increasing by between 9% and 67% when compared to the Land Type dataset. The value of the improved soil maps is, however, highlighted through the enhanced spatial detail of streamflow generation mechanisms and water balance components. The internal catchment processes are represented more accurately, and we argue that South Africa needs a detailed hydrological soil map for effective water resource management.

Resumen En este trabajo se cuantifican tendencias de aumento de suelo urbanizado en la ciudad de Tunja, Colombia, para modelar escenarios futuros. El modelo se basa en la clasificación de imágenes satelitales y en la inclusión de factores influyentes en el urbanismo. La visualización de las zonas probables de desarrollo se logra a partir de tres etapas. 1). Preprocesamiento, en la que se define la zona de estudio y adecúa las imágenes. 2). Procesamiento, en la que se clasifican las imágenes 2000, 2012 y 2017 y se generan mapas de coberturas y usos: urbanizado, zona verde y área abierta. 3). Postprocesamiento, en la que se valida la precisión de la clasificación. 4). Modelamiento de escenarios futuros, en la que se incorporan los factores de cambio hacia suelo urbanizado y las restricciones, se genera un análisis de cambio y uno de áreas potenciales de transición a territorio urbanizado, para crear los modelos predictivos 2017, 2025 y 2030. El modelo se valida comparando la predicción 2017, con la imagen de clasificación del mismo año, modificando factores hasta que la imagen de predicción 2017 sea representativa de la imagen producto de clasificación.

Abstract This article quantifies the trends in the growth of urbanized land in Tunja city, Colombia, with the aim of modelling future scenarios. The modeling is based on the satellite images classification and the inclusion of the driving factors in the urban development. The view of the viable development areas is achieved through the following stages. 1). The preprocessing, which defines the study area and adapts the images. 2). The processing, which classifies the images of years 2000, 2012 and 2017 and generates coverage and use maps: urbanized, green zone and open area. 3). The postprocessing, in which the accuracy of the classification of images is validated. 4). The Modeling of future scenarios, that incorporates factors of change and restrictions towards urbanized areas. It generates the analysis of change and potential areas of transition to urbanized areas, providing predictive data for 2017, 2025 and 2030. The modeling is validated comparing the 2017 prediction with the classiication image of the same year and then, modifying factors until the 2017 prediction image is representative of the classiication image.

Résumé Dans ce travail, il se quantifie les tendances de l'augmentation des sols urbanisées à Tunja, en Colombie, sont modélisé dans scénarios futurs. Le modèle est basé sur la classification des images satellites et l'inclusion des facteurs d'influence dans la planification urbaine. Les zones probables de développement sont visualisées à travers les étapes: 1). Prétraitement, pour définir la zone d'étude et ajuste les images. 2). Le traitement, pour classifier les images 2000, 2012 et 2017, générer des cartes de couverture et d'utilisation: urbanisé, espace vert et espace ouvert. 3). Post-traitement, pour valider l'exactitude du classement. 4). La modélisation des scénarios futurs pour integrer les facteurs de changement vers les terres urbanisées et les restrictions, générer une analyse des changements et l'une des zones potentielles de transition vers le sol urbanisé, et pour créer les modéles prédictifs 2017, 2025 et 2030. Le modèle est validé en comparant la prédiction 2017, avec l'image classiiée de la même année, et en modifiant les facteurs jusqu'à ce que l'image de prédiction 2017 soit représentative de l'image du produit de la classiication.

Resumo Neste trabalho são quantificadas as tendências no aumento da urbanização do solo na cidade de Tunja, Colômbia para o modelamento dos cenários futuros. O modelo baseia-se na classificação de imagens satelitais e na inclusão de fa-tores de influência para o planejamento urbano. A visualização das áreas prováveis de desenvolvimento no futuro consegue-se a partir do desenvolvimento das seguintes etapas: 1) Pré-processamento para definição da área de estudo e ajuste das imagens. 2) Processamento, com a classificação das imagens dos anos 2000, 2012 e 2017, além da geração de mapas de coberturas e usos dos solos: urbanizado, zonas verdes e áreas abertas. 3) Post-processamento, etapa na qual valida-se a precisão da classificação assignada. 4) Modela-mento dos cenários futuros, com a incorporação dos fato-res de mudança para solos urbanizados e suas restrições. Nesta etapa gera-se uma análise de mudança e uso de áreas potenciais de transição para território urbanizado, visando a criação de modelos preditivos para os anos 2017, 2025 e 2030. O modelo é validado comparando a predição para 2017 com a imagem de classificação correspondente ao mesmo ano, fazendo a modificação dos fatores, até conseguir que a imagem de predição 2017 seja representativa da imagem produto da classiicação.

Abstract Changes in land use and land cover (LULC) can result in significant changes in a hydrographic basin flow regime. Future projections about LULC and its interference with water availability help to identify extreme events in advance and help propose appropriate management measures. Thus, this study aimed to make the LULC projection for the year 2030 for the Alto Rio Grande (ARG) sub-basin, located in Southeastern Brazil. This region was chosen because of its intense water resources use and for having recently faced water scarcity as result of prolonged droughts and inadequate water resources management. To identify the LULC trend for the year 2030, the Land Change Modeler (LCM) was used, the map obtained was inserted in the Soil and Water Assessment Tool (SWAT) model previously calibrated and validated for the region’ environmental and climatic conditions. The ARG sub-basin was affected by heavy rains in 2011, which resulted in changes in the landscape due to landslides. This particularity of the region contributed to the projection of LULC for the year 2030 to present an increase in forest and pastures to the agricultural areas detriment. When evaluating the impacts of these changes in water availability, it was observed that the SWAT model presented, for the same rainfall conditions, a reduction in peak streamflows of up to 59% and a reduction in the average monthly flow of up to 63% in 2030 in relation to the LULC observed in 2017. Thus, this study provides an important contribution by identifying a considerable reduction in water availability. These results will help to formulate strategies for water resources management and the adoption of measures to promote water security in the region.

Resumen Los cambios en el uso y la cobertura del suelo pueden resultar en cambios significativos en el régimen del flujo de una cuenca hidrográfica. Los estudios predictivos sobre el uso del suelo y su interferencia con la disponibilidad del agua ayudan a identificar eventos extremos con anticipación a fin de proponer medidas de gestión adecuadas. De esta forma, este estudio tuvo como objetivo realizar la predicción del uso del suelo para el año 2030 para la subcuenca del Alto Río Grande (ARG), ubicada en el sureste de Brasil. Esta región fue elegida por el uso intenso de los recursos hídricos y por haber enfrentado, recientemente, escasez de agua como resultado de sequías prolongadas y una gestión inadecuada de los recursos hídricos. Para la predicción del uso del suelo en 2030 se utilizó el Land Change Modeler (LCM), el mapa obtenido se insertó en el modelo Soil and Water Assessment Tool (SWAT) previamente calibrado y validado para las condiciones ambientales y climáticas de la región. La subcuenca ARG fue afectada por fuertes lluvias en 2011 que resultaron en cambios en el paisaje debido a deslizamientos de tierra. Esta particularidad de la región contribuyó para que la predicción del uso del suelo para el año 2030 presente un aumento de bosques y pastos en detrimento de las áreas agrícolas. Al evaluar los impactos de estos cambios en la disponibilidad del agua, se observó que el modelo SWAT presentó, para las mismas condiciones de precipitación, una reducción en los caudales pico de hasta 59% y una reducción en el caudal promedio mensual de hasta 63% en 2030 en relación con el uso del suelo observado en 2017. Es decir, este estudio hace un aporte importante al identificar una reducción considerable en la disponibilidad del agua. Estos resultados ayudarán a formular estrategias para la gestión de los recursos hídricos y la adopción de medidas para promover la seguridad hídrica en la región.

Volhoubare ontwikkeling is die kern van stadsbeplanning en verstedeliking speel 'n sentrale rol in die bereiking van doelwitte vir volhoubare ontwikkeling. Verstedeliking is egter verweef met eksistensiële uitdagings soos klimaatsverandering. Die Nasionale Regering het 'n oorvloed van nasionale planne ontwikkel om volhoubare ekonomiese ontwikkeling te bevorder, wat gelei het tot 'n oorvloed wette wat baie statutêre vereistes aan munisipaliteite stel. Hierdie artikel bevat 'n kritiese oorsig van hierdie nasionale planne, die statutêre vereistes en die gevolglike beplanningsraamwerke en -instrumente. Die belangrikste bevindinge is dat baie nasionale planne nie voldoende vordering gemaak het nie en dat handelinge en beplanningsinstrumente nie vereis dat beleidsingrypings of langtermynvisies voor implementasie getoets word nie. Dit kan bydra tot fragmentasie, swak koördinasie en die verwaarlosing van die impak daarop deur klimaatsverandering. Gevallestudies gebaseer op simulasiemodelle wat plaaslik as besluitsteuninstrumente gebruik word, word aangebied voordat 'n saak gemaak word vir die gebruik van Geïntegreerde Grondgebruik- en Vervoermodelle om beleidsingrypings te toets wat stedelike en klimaatsbeplanning insluit. 'n Verbeterde simulasie-optimeringsraamwerk word voorgestel om beplanners in staat te stel om die beste manier te bepaal om spesifieke teikens te bereik. Hierdie raamwerk is nuttig aangesien baie staatsdepartemente weet 'wat' hulle wil bereik, maar dikwels sukkel om te bepaal 'hoe' om hierdie teikens te bereik, wat nog te sê of dit selfs haalbaar is.

Nts'etsopele ea moshoelella ke khubu ea meralo ea litoropo, 'me ho aha litoropo ho bapala karolo ea mantlha ho flhlelleng Maikemisetso a Nts'etsopele ea Moshoelella. Ho fallela litoropong, leha ho le joalo, ho hokahane le mathata a teng joalo ka phetoho ea maemo a leholimo. Mmuso o hlahisitse meralo e mengata ho feta tekano ea naha bakeng sa ho hodisa ntshetsopele ea moruo ea moshwelella, e leng se lebisitseng ho letoto le behang litlhoko tse ngata tsa molao ho bomasepala. Sengoliloeng sena se fana ka tlhahlobo e hlokolosi ea meralo ena ea naha, litlhoko tsa molao, le lisebelisoa tsa moralo. Liphuputso tse ka sehloohong ke hore meralo e mengata ea naha ha ea ka ea flhlela tsoelo-pele ho lekana, le hore melao le meralo ea thero ea litoropo ha li hloke litsenyehelo tsa maano kapa ponelo-pele ea nako e telele hore li lekoe pele li kenngoa ts'ebetsong. Sena se ka kenya letsoho ho arohaneng, ho se hokahaneng hantle, le ho hlokomoloha litla-morao tsa phethoho ea maemo a leholimo. Liphuputso li ipapisitse le mehlala ea lipapiso tse sebelisoang metseng e le ho tsehetsa liqeto pele moralo oa Kopanelo ea Tsebeliso ea Mobu le Lipalangoang o ka kenngoa tshebetsong. Sena ke teko ea maano a kenyeletsang moralo oa litoropo le moemo a leholimo. Sengoliloeng se sisinya Moralo o ntlafalitsoeng oa ketsiso ele ho lumella baetsi ba meralo ho fumana mekhoa e metle ea ho flhlela lipheo tse itseng. Moralo ona o na le thuso kaha mafapha a mangata a 'muso a tseba seo a lakatsang ho se flhlela, empa hangata a sokola ho tseba hore na lipehelo tsena li ka fihleloa joang, re se re sa re letho ka hore na li ka finyeNoa kapa che.

Sustainable development is at the heart of city planning, and urbanisation plays a central role in achieving the Sustainable Development Goals. Urbanisation, however, is interlaced with existential challenges such as climate change. The National Government has developed an overabundance of national plans to foster sustainable economic development, which has led to a plethora of acts that place many statutory requirements on municipalities. This article contains a critical review of these national plans, the statutory requirements, and the resultant planning frameworks and instruments. The main findings are that many national plans did not make adequate progress and that acts and planning instruments do not require policy interventions or long-term visions to be tested before being implemented. This might contribute to fragmentation, poor coordination, and neglecting the impact of climate change. Case studies based on simulation models being used locally as decision-support tools are presented before a case is made for the use of Integrated Land Use and Transport models to test policy interventions that include urban and climate planning. An enhanced simulation-optimisation framework is proposed to allow planners to determine the best means to achieve specific targets. This framework is useful as many government departments know 'what' they wish to achieve, but often struggle to determine 'how' to achieve these targets, let alone whether they are even achievable.

The effects of climate change on water resources could be numerous and widespread, affecting water quality and water security across the globe. Variations in rainfall erosivity and temporal patterns, along with changes in biomass and land use, are some of the impacts climate change is projected to have on soil erosion. Sedimentation of watercourses and reservoirs, especially in water-stressed regions such as sub-Saharan Africa, may hamper climate change resilience. Modelling sediment yield under various climate change scenarios is vital to develop mitigation strategies which offset the negative effects of erosion and ensure infrastructure remains sustainable under future climate change. This study investigated the relative change in sediment yield with projected climate change using the Soil and Water Assessment Tool (SWAT) for a rural catchment in South Africa for the period 2015-2100. Data from six downscaled Coupled Global Climate Models (CGCM) were divided into three shorter time periods, namely, 2015-2034, 2045-2064 and 2081-2100. Results were then compared with a control scenario using observed data for the period 2002-2017. The results show that, if left unmanaged, climate change will likely lead to greater sediment yield, of up to 10% more per annum. Peak sediment yield will also increase almost three-fold throughout the century. The study shows that projected climate change will have multiple negative effects on soil erosion and emphasised the need for changes in climate to be considered when embarking on water resource developments.

El embalse Milluni Grande depende principalmente de la precipitación, siendo vulnerable ante periodos de sequía, de forma que puede afectar a la seguridad hídrica de las ciudades de La Paz y El Alto. Por lo tanto, el presente estudio busca determinar la variación de la cantidad de agua disponible en el embalse bajo el set de escenarios de cambio climático establecidos en el quinto informe del Panel Intergubernamental sobre el Cambio Climático (IPCC) para el periodo 2022-2090. El área de estudio se limitó a la microcuenca Milluni, tomando el embalse Milluni Grande como punto de desemboque. La modelación hidrológica se realizó mediante la herramienta Water Evaluation and Planning System (WEAP) utilizando el ensamble de datos diarios de precipitación y temperatura generado a través de la herramienta Gridded Meteorological Ensemble Tool (GMET). Se incorporaron los escenarios de cambio climático empleando el Modelo 1 del Sistema Terrestre de Noruega NorESM1-M, reduciendo su escala mediante el método no paramétrico de vecinos más cercanos (knn-bootstrap). Se obtuvieron las siguientes tendencias para el periodo y área de estudio: incremento general de temperatura, incremento de precipitación en época seca y reducción de precipitación en época húmeda, lo cual puede generar situaciones de sequía. Por otra parte, el caudal de entrada al embalse Milluni Grande tiene tendencia a variar de forma directamente proporcional a la precipitación, mientras que su volumen tiene tendencia a reducirse. Asimismo, puede existir un déficit en la cobertura de los requerimientos de los sitios de demanda, llegando a valores mínimos de 45% para el sistema de distribución Achachicala y 27% para el sistema Meseta. Todos los resultados son acentuados en el escenario pesimista RCP 8.5.

The Milluni Grande reservoir depends mainly on precipitation, being vulnerable to drought periods, which may affect the water security among La Paz and El Alto cities. Therefore, the present study sought to determine the variation of water available in the reservoir under the set of climate change scenarios stablished on the fifth report of the Intergovernmental Panel on Climate Change (IPCC) for the period 2022-2090. The study area was limited to the Milluni microbasin, taking the Milluni Grande reservoir as the outlet point. The hidrological modelling was performed through the Water Evaluation and Planning System (WEAP) using the temperature and precipitation daily data ensemble generated with the Gridded Meteorological Ensemble Tool (GMET). Climate change scenarios were incorporated using the Model 1 of Norway Land System NorESM1-M, reducing its scale through the nearest neighbor non-parametric method (knn-bootstrap). The following tendencies were obtained for the study period and area: overall temperature rise, precipitation rise during the dry seasons and precipitation reduction during the wet seasons, which might cause drought situations. On the other hand, the Milluni Grande inlet flow tends to vary proportionally to the precipitation, while its volume tends to decrease. In addition, a deficit in the coverage of the requirements of demand sites might exist, reaching minimum values of 45% for the Achachicala distribution system and 27% for the Meseta system. All results are accentuated in the pessimistic scenario RCP 8.5.

Resumo Os índices de vegetação obtidos por modelos, aplicados em imagens orbitais, são comumente utilizados para o monitoramento da cobertura do solo, sendo importantes para registrar alterações na biomassa, identificação do ciclo fenológico, relação com o sequestro de carbono e indicadores de mudanças climáticas. Na região do bioma Caatinga, a compreensão em escalas local e diária dos fenômenos que ocorrem na cobertura do solo é muito importante devido à sua heterogeneidade, sazonalidades e às múltiplas ações humanas. Neste ambiente, cresce a importância da representação temporal e espacial. Os satélites da série Landsat apresentam características adequadas para representar as variações espaciais, mas têm uma baixa amostragem temporal. Nesse sentido, o presente estudo tem como objetivo melhorar a representação temporal dos dados capturados pelos satélites Landsat para uma região do bioma Caatinga. Funções de três parâmetros são avaliadas para representação temporal matemática do Índice de Vegetação por Diferença Normalizada (NDVI), tendo a sua avaliação de desempenho realizada a partir dos parâmetros estatísticos qui-quadrado reduzido (χ2) e coeficiente de determinação (R2). A análise considera o estado de alteração da cobertura do solo pela ação antrópica e o regime pluviométrico anual. A função Cauchy apresentou melhor desempenho, ajustando-se bem a 83% dos anos e locais analisados, obtendo um R2 médio de 0,82. Os parâmetros da função de melhor desempenho identificada neste estudo podem ser uma valiosa fonte de informações para estudos ambientais na Caatinga que precisem avaliar o comportamento temporal da vegetação.

Abstract Vegetation indexes from remote sensing images are often used for land-cover monitoring and identification of biomass changes. They are also very useful to describe the relationships between the phenological cycle and the carbon sequestration, which are climate change indicators. The Caatinga land-cover is very heterogeneous, making hard the understanding of the land cover processes in different scales (spatial and temporal), due to seasonalities and human actions. The Landsat series products usually can describe spatial land-cover variations, with a low temporal scale, so far. This study aims to improve the temporal representation of the land cover by Landsat images for a Caatinga area. This article presents an evaluation, using a mathematical approach of three-parameter functions to describe the Normalized Difference Vegetation Index (NDVI). Each function performance was evaluated by the reduced chi-square (χ2) and determination coefficient (R2) parameters. The analysis is performed for an annual period and considers land-cover changes by anthropic action. The Cauchy function seems the best option and presented an adjust up to 83% of the total (years and places), with an R2 (average) of 0.82. The parameters of this function can be a valuable source for environmental studies in the Caatinga biome, supporting temporal analysis of the vegetation.

Resumo: O desenvolvimento de estratégias que conciliem atividades antropogênicas com a conservação da natureza tem se tornado cada vez mais urgente, principalmente em regiões que enfrentam uma rápida conversão da vegetação nativa em agricultura. Modelos conceituais permitem avaliar como fatores antropogênicos (por exemplo, mudança de uso e cobertura do solo e mudanças climáticas) modificam os processos naturais, sendo uma ferramenta útil para apoiar a tomada de decisões estratégicas. O presente trabalho descreve um modelo conceitual para avaliar a provisão de serviços ecossistêmicos relacionados à água sob diferentes cenários de uso do solo na região de Matopiba, no Cerrado, a savana com maior biodiversidade do mundo e uma fronteira agrícola. Foram determinadas as variáveis do modelo (fatores diretos, fatores indiretos, componentes focais e respostas) e o Nature Futures Framework foi consultado para incorporar componentes socioeconômicos e feedbacks. Cenários futuros foram desenvolvidos considerando possíveis trajetórias de fatores antropogênicos e respostas de governança que podem impactar o uso do solo na região, incluindo a possibilidade de cumprimento total do Código Florestal e a implementação da Moratória da Soja na região. O modelo conceitual e os cenários apresentados no presente trabalho podem ser úteis para melhorar a compreensão das complexas interações entre fatores antropogênicos, serviços ecossistêmicos relacionados à água e suas possíveis implicações para os sistemas naturais e sociais da região. Decisões de governança serão críticas para manter os ecossistemas da região, os serviços fornecidos por eles, a cultura e tradição das pessoas historicamente inseridas na paisagem. Em reconhecimento da dependência da humanidade em relação à natureza, destaca-se a importância de inverter a maneira como os cenários são usualmente usados. Em vez de mensurar os impactos de diferentes políticas na natureza, cenários representando os resultados desejados para biodiversidade e serviços ecossistêmicos podem ser usados para informar como políticas podem garantir a integridade dos ecossistemas no futuro.

Abstract: The development of strategies that conciliate anthropogenic activities with nature conservation is becoming increasingly urgent, particularly in regions facing rapid conversion of native vegetation to agriculture. Conceptual modelling enables assessment of how anthropogenic drivers (e.g. land use/land cover change and climate change) modify natural processes, being a useful tool to support strategic decision-making. The present work describes a conceptual model to evaluate water-related ecosystem service provision under different land use scenarios in the Matopiba region of the Brazilian Cerrado, the world’s most biodiverse savanna and an agricultural frontier. Model variables were determined (direct drivers, indirect drivers, focal components and responses) and the Nature Futures Framework was consulted to incorporate socio-ecological components and feedbacks. Future scenarios were developed considering potential trajectories of drivers and governance responses that may impact land use in the region, including the possibility of full compliance with Forest Code and implementation of the Soy Moratorium in the region. The conceptual model and scenarios developed in the present study may be useful to improve understanding of the complex interactions among anthropogenic drivers, water-related ecosystem services and their potential repercussions for natural and social systems of the region. Governance decisions will be critical to maintaining the ecosystems of the region, the services it provides and the culture and tradition of the people historically embedded in the landscape. In acknowledgment of humanity’s dependence on nature, the importance of inverting the way scenarios are used is highlighted. Rather than using scenarios to measure the impacts of different policy options on nature, scenarios representing the desired outcomes for biodiversity and ecosystem services can be used to inform how policies can guarantee ecosystem integrity into the future.

Abstract The potential effects of climate change and land use change make it essential to assess the processes of erosion and sediment transport in current and future situations. However, evaluating these processes correctly is not easy, because there is no information for the calibration and validation of mathematical models. This research proposes a methodological alternative for the calibration of a sedimentological model in basins without information and for modeling these processes, including the effects of climate change and land use change. The results foresee an increase in runoff (up to 1 m3s-1) in the future as well as reductions in the transport of sediments (0.0003 m3s-1) and erosion (5%), compared to the current one in the Turbio river sub-basin.

Resumen Ante los potenciales efectos del cambio climático y el cambio de uso de suelo, resulta transcendental evaluar los procesos de erosión y de transporte de sedimentos en condiciones actuales y futuras. Sin embargo, evaluar correctamente estos procesos no es una tarea sencilla debido a que en la mayoría de los casos no se cuenta con información observada de sedimentos para la calibración y validación de modelos matemáticos. Por ello, esta investigación plantea una alternativa metodológica para el modelado de estos procesos en cuencas sin información, incluyendo los efectos del cambio climático y cambio de uso de suelo. Los resultados obtenidos pronostican en el futuro cercano un aumento de los caudales (hasta 1 m3s-1) así como reducciones en el transporte de sedimentos (0.0003 m3s-1) y en la erosión (5%), respecto de la registrada actualmente en la subcuenca del río Turbio.

Resumo Neste artigo trabalhamos uma metodologia combinada de sensoriamento remoto, modelagem ambiental e ecologia da paisagem para análise dos impactos da expansão do reflorestamento com eucalipto na estrutura da paisagem. O uso combinado dessas técnicas possibilitou a simulação de cenários futuros, utilizando-os não apenas como uma ferramenta de análise, mas, sobretudo, para auxiliar no planejamento. O trabalho teve como área de estudo os municípios da Bacia do Rio Piracicaba e da Região Metropolitana do Vale do Aço, região que abriga importantes indústrias do setor siderúrgico, de papel e celulose em Minas Gerais. Foram utilizados dados da cobertura da terra obtidos a partir de classificações de imagens de satélite (TM/landsat) para os anos de 1985, 2010 e 2013. Em conjunto à cobertura da terra foram exploradas diversas fontes de variáveis estimuladoras e restritivas à mudança para criação de um modelo de cobertura da terra capaz de simular a expansão das áreas de eucalipto considerando um cenário de manutenção da tendência de crescimento observada entre 1985 e 2010. Os resultados do mapeamento mostraram que entre 1985 e 2010 houve aumento de cerca de 12% nas áreas de reflorestamento com Eucalipto, ao passo que as áreas de floresta diminuíram aproximadamente 9% e as de pastagem 3%.

Abstract This paper combines remote sensing, environmental modeling, and landscape ecology to investigate the impacts of the expansion of eucalyptus reforestation. Using these techniques, a methodology was developed to analyze and predict future land cover and landscape structure trends. The study area was comprised of the river basin municipalities in Rio Piracicaba and the metropolitan region of Vale do Aço (RMVA), a region that is home to large steel, paper, and cellulose industries in Minas Gerais. This major hub of economic development in the state has altered the landscape through deforesting native vegetation and planting eucalyptus trees. Land cover data were taken from satellite image classifications (TM/Landsat) from 1985, 2010 and 2013 in order to study the land cover changes. A number of variables that stimulate or restrict these alterations and the eucalyptus expansion observed between 1985 and 2010 were used to simulate the eucalyptus expansion, through Multi-Layer Perception Neural Networking. The results showed that the areas of Eucalyptus reforestation increased by about 12% between 1985 and 2010, whereas forest areas contracted by approximately 9%, and pasture by 3%. The simulated eucalyptus expansion indicated that by 2035 the structure of the landscape will have changed, with an increased level of isolation of the forest patches and a decrease in their nuclear area.

Resumen En este artículo trabajamos una metodología combinada de teledetección, modelado ambiental y ecología del paisaje para analizar los impactos de la expansión de la reforestación con eucalipto en la estructura del paisaje. El uso combinado de estas técnicas posibilitó la simulación de escenarios futuros, utilizándolos no sólo como una herramienta de análisis, sino, sobre todo, para auxiliar en la planificación. El trabajo tuvo como área de estudio los municipios de la Cuenca del Río Piracicaba y de la Región Metropolitana del Valle del Acero, región que alberga importantes industrias del sector siderúrgico, de papel y celulosa en Minas Gerais. Se utilizaron datos de la cobertura de la tierra obtenidos a partir de clasificaciones de imágenes satelitales (TM / landsat) para los años 1985, 2010 y 2013. En conjunto con la cobertura de la tierra se exploraron diversas fuentes de variables estimuladoras y restrictivas al cambio a la creación de un modelo de cobertura de la tierra capaz de simular la expansión de las áreas de eucalipto considerando un escenario de mantenimiento de la tendencia de crecimiento observada entre 1985 y 2010. Los resultados del mapeamiento mostraron que entre 1985 y 2010 hubo aumento de cerca del 12% en las áreas de reforestación con Eucalipto, mientras que las áreas de bosque disminuyeron aproximadamente 9% y las de pastoreo 3%.

ABSTRACT For many years the Malaysian oil palm (Elaeis guineensis Jacq.) industry has been facing the challenge of the reduced rate of palm oil yield caused by the gap in the oil palm production and high land usage. In the oil palm industry, modelling and selecting variables play a crucial role in apprehending different issues, i.e. decision making. Nonetheless, the advance in computer technology has created a new opportunity for the study of modelling as selecting variables intended to choose the "best" subset of predictors. Owing to this great interest in the predictions, the study aims to develop a genetic algorithm (GA) to identify the relevant variables and search for the best combinations for modelling to examine the potential of oil palm production in Sarawak and Sabah, Borneo, Malaysia, under a given set of assumptions. Eleven years of high climatic change and air pollution are utilized to secure findings where the primary variable, i.e. the evaporation and surface wind speed, were recorded on the proportion of effect reached up to 100% in Sarawak and Sabah, respectively. Moreover, models were built on the basis of variables that have been selected by the GA. Across the optimization, procedures obtained the best Two Factor Interaction (2FI) models to achieve the best model of oil palm productivity prediction with a value of R2 of 0.948, mean squared error of 0.022, and the model P-value of < 0.0001 in Sabah. This research concludes that the GA method is a user-friendly variable selection tool with excellent results because it can choose variables correctly.

Design flood estimation (DFE) is essential in the planning and design of hydraulic structures. In South Africa, outdated methods are widely applied for DFE. In this paper the potential of a continuous simulation modelling (CSM) approach to DFE in South Africa, using the daily time-step ACRU agrohydrological model, is investigated. The paper focuses on the links and similarities between the SCS-SA and ACRU models and the subsequent preliminary investigations that were undertaken to account for and incorporate the land cover classes, including land management practices and hydrological condition, of the SCS-SA model into the ACRU CSM approach. The approach to this study was to investigate how design volumes simulated by the SCS-SA model for various land management practices or conditions could be simulated by the ACRU model. Since peak discharge estimation in both models is directly dependent on simulated volumes, this preliminary study focused only on design runoff volumes, with subsequent investigations on peak discharge required in future research. In the absence of observed data, design runoff volumes and changes in design runoff volumes, as simulated by the SCS-SA model, were used as a substitute for observed data, i.e., as a reference, to achieve similar design runoff volumes and changes in design volumes in the ACRU model. This was achieved by adjusting relevant input parameters in the ACRU model to represent the change in management practice or hydrological condition, as represented in the SCS-SA model. Following a sensitivity analysis of relevant ACRU parameters, calibration of 2 selected parameters against SCS-SA CN values for selected land cover classes was performed. A strong linear relationship (R² = 0.94) between these ACRU parameters and SCS-SA CNs for selected land cover classes was found and consequently specific rules and equations were developed to represent SCS-SA land cover classes in ACRU. Recommendations are made to further validate and verify the approach and to further the development of a CSM system for DFE in South Africa.

ABSTRACT Water availability restrictions are already a reality in several countries. This issue is likely to worsen due to climate change, predicted for the upcoming decades. This study aims to estimate the impacts of climate change on groundwater system in the Guarani Aquifer outcrop zone. Global Climate Models (GCM) outputs were used as inputs to a water balance model, which produced recharge estimates for the groundwater model. Recharge was estimated across different land use types considering a control period from 2004 to 2014, and a future period from 2081 to 2099. Major changes in monthly rainfall means are expected to take place in dry seasons. Most of the analysed scenarios predict increase of more than 2 ºC in monthly mean temperatures. Comparing the control and future runs, our results showed a mean recharge change among scenarios that ranged from ~-80 to ~+60%, depending on the land use type. As a result of such decrease in recharge rates, the response given by the groundwater model indicates a lowering of the water table under most scenarios.

Conceptual rainfall-runoff models have become a basic tool for evaluating effects of land use/cover changes on the hydrologic processes in small-scale as well as large watersheds. The runoff-producing mechanism is influenced by land use/cover changes. In this study, we analysed the effect of land use change on hydrological model parameters by calibrating the model parameters of different time periods with different land use via a linearized calibration method. The parameter calibration of a conceptual model usually involves the construction of objective function and optimization methods for good performance of observed data. However, the objective function of the minimum-sum-squared error will introduce an unrelated optimum solution for the parameter calibration problem of a conceptual model, which belongs to a highly complex nonlinear system. Thus, a linearized parameter calibration method, which searches for the optimal value on a parameter surface, is presented, based on the analysis of the problems of the objective function of the minimum-sum-squared error. Firstly, an ideal model is shown that illustrates the efficiency and applicability of this method. Secondly, the novel method is demonstrated for solving the Xinanjiang daily model parameter calibration. Finally, 50 years of data are divided into 4 different periods for parameter comparison, through which the effects of land use/cover changes on runoff in Dapoling watershed are evaluated. The results show that the linearized parameter calibration method is convergent, reasonable and effective. For example, the model parameter of evapotranspiration coefficient KC varied considerably, from 0.658 to 0.922, in response to land use/cover change within the watershed.

A região semiárida do Nordeste brasileiro tem sofrido os impactos das mudanças ora causadas por ações humanas, ora causadas direta ou indiretamente pelas mudanças no clima. O zoneamento de áreas mais suscetíveis a mudanças ou historicamente sob forte pressão por causa do crescimento das cidades e outros fatores antrópicos pode auxiliar em ações de planejamento mais sustentáveis nesta região. Este trabalho apresenta uma metodologia integradora para correlacionar diferentes variáveis (demográficas, climáticas e socioeconômicas) de forma a indicar áreas submetidas a potencial “pressão” por mudanças na região. A utilização de um estimador estatístico para uniformização das informações, através de modelagem em ambiente SIG, sobrepondo as variáveis consideradas, possibilitou uma integração eficiente. Os resultados apontam áreas submetidas a “forte pressão” no entorno de cidades importantes no contexto atual do semiárido nordestino, o que se reflete em alterações marcantes na forma de uso e ocupação destas regiões. Isto se configura, principalmente, por essas regiões apresentarem alta densidade populacional, acompanhada por um crescimento do PIB agropecuário nos últimos anos.

The semiarid region of Northeastern part of Brazil is under changes pressures driven by human activities or climate changes. Spatial analysis and visualization of potential land use/land cover changes (LULCC) zones can be a useful tool for helping on planning actions or decision making policies for sustainable development. This study presents a methodological and spatial approach for pointing out mainly changes drivers. GIS tools and a statistics estimator are used in a spatial modelling and standardization of all inputs from different data sources. The results show the nearest areas from some important middle cities such as “high pressure changes”. In those areas, it is possible to observe the strong correlation between LULCC and high density urban areas and an increasing of GDP (Gross Domestic Product for Livestock and Agriculture) in the last years as well.