Mitigasi Dan Adaptasi Bencana Banjir di Kecamatan Pallangga Kabupaten Gowa

Bencana banjir yang terjadi secara terus-menerus dapat menyebabkan berbagai kondisi yang apabila terjadi dapat menimbulkan berbagai kerentanan yang memerlukan pemikiran yang lebih dalam untuk mengantisipasi bencana banjir. Mitigasi dan Adaptasi Bencana Banjir di Kecamatan Pallangga Kabupaten Gowa bertujuan untuk memetakan tingkat kerentanan bencana banjir dan upaya mitigasi dan adaptasi yang tepat berdasarakan tingkat kerentanan bencana banjir di Kecamatan Pallangga. Sejalan dengan tujuan penelitian ini maka dalam penelitian ini menggunakan metode penelitian deskriptif kualitatif, untuk menentukan tingkat kerentanan dengan analisis spasial overlay dan skoring parameter penentu kerentanan banjir. Hasil dari penelitian ini adalah Kecamatan Pallangga diklasifikasi dalam tiga tingkat kerentanan bencana banjir meliputi rentan tinggi, rentan sedang dan rentan rendah serta arahan mitigasi dan adaptasi bencana banjir berdasarkan tingkat kerentanan. The floods disasters that occur continuously can cause various conditions which can cause a variety of vulnerabilities that require deeper thought to anticipate. Flood mitigation and adaptation in Pallangga District of Gowa aims to map the level of flood vulnerability and provide mitigation and adaptation directions based on the level of flood vulnerability in Pallangga. This research uses descriptive qualitative research methods, to determine the level of vulnerability with spatial overlay analysis and weight scoring of parameters determining flood vulnerability. The results of this research are in Pallangga classified into three levels of vulnerability to flood disasters including high vulnerability, medium vulnerability and low vulnerability with directives flood mitigation and adaptation based on the level of vulnerability.

LAND USE POLICY AREA (LUPA) CONCEPT MODEL

The paper presents a Land Use Policy Area (LUPA) Concept Model adding the three basic elements: (i) ecosystem-based land use regarded as the intersection of the ecosystem and land use elements, (ii) subwatershed-based land use as the intersection of the subwatershed and land use elements, and (iii) integrated environmental management is the intersection of the subwatershed and ecosystem elements regarded as the Integrated Ecosystem Development Planning Unit (IE-DPU). The basic (spatial) elements are mathematically expressed as the paired sets of the three main variables, namely: ecosystem (dependent), watershed (dependent) and land use (independent) variables. The challenging work in this study was the development of a geospatial information model for use in policy areas LUPA applying these variables. There are four steps applied to answer the research objective, these are: ecological zone assessment, ridge-to-reef watershed delineation, land and water use heads-up mapping, ecosystem-based land use overlay analysis, watershed-based land use overlay analysis, integrated environmental management overlay analysis, and LUPA overlay analysis. The concept model analysis steers the geospatial information modeling for LUPA which carried the intersections of the paired variables: ecosystem-based land use, subwatershed-based land use and integrated environmental management as variating inputs to process by extracting the science-based information (overlay output) which practically highlighted the LUPA classification: (i) Protection with 49.1% or 3858.2 Ha of mangrove forest reserve and water use, (ii) Production areas with 46.5% or 3631.7 Ha mostly agricultural and aquacultural areas, (iii) Settlement with 2.7% or 209.2 Ha of urban and urban uses, and (iv) Infrastructure with 1.5% or 116.7 Ha of development. The authors concluded that land use policy areas will relatively change as land use changes which is also seen reliant on the impacts of climate change.

Exploration of groundwater potential zones using analytical hierarchical process (AHP) approach in the Godavari river basin of Maharashtra in India

Total natural and groundwater resources play the most crucial role in developing ecological, biological and socioeconomic doings. Various parameters like land use, geology, elevation, slope, lineament, lineament density, drainage density and geomorphology affect the groundwater development of recharge and its accessibility. In this research, geographical information system (GIS), remote sensing, weighted overlay analysis and analytical hierarchy process (AHP) methods have been used for groundwater prospects mapping, and identifying suitable solutions site for soil and water conservation structures. To calculate the weights were assigned to every layers component in the determination of affecting factors. The weighted overlay analysis (WOA) tool is applied to give the sub-parameter ratings based on the scientific literature. The final map of potential groundwater zone map has prepared using Arc GIS 10.1 software and AHP methods. About 49.71% of the areas fall under the 'good potential zone, 41.05% falls under the 'moderate potential zone', and 9.22% falls under the 'poor zone by using AHP technique. Groundwater potential zone map is depend on the weighted overlay analysis and analytical hierarchy process (AHP) methods. The highest GWP is located in the lower part of the basin due to the best surface runoff gathering, infiltration situations and subsurface storage volume. The present study procedure, methods and outcomes can be valuable to estimate the suitable groundwater zones parallel to improve the dry land area in the semi-arid and arid regions of India.

Mapping Potential Zones for Groundwater Recharge Using a GIS Technique in the Lower Khwae Hanuman Sub-Basin Area, Prachin Buri Province, Thailand

The lower Khwae Hanuman sub-basin in Thailand suffers from water shortage during each dry season. As such, groundwater resources are an additional freshwater source in this region, in particular for cultivating activities. Thus, an understanding of the volume of groundwater recharge into the saturated zone is required. The objective of the study is to assess the groundwater recharge potential (GRP) using the weighted overlay analysis method by geographic information system (GIS) and finally checking the reliability of GRP map using observed specific capacity carried out by the Department of Groundwater Resources (DGR). The geological and hydrogeological features that affect groundwater potential are the lithology, land use, lineaments, drainage, slope, and soil. The weighting and rating of these six influencing factors were determined by assessing the interrelationship of the main and minor influences of each factor based on several literature reviews, followed by a weighted overlay analysis with GIS, in association with groundwater recharge. The GRP can be classified in descending order: high, moderate, low, and very low, where about 33.9 km2 (2.26% of the total area of 1,500 km2) had high recharge potentiality, located at the center of the area. Only 12.8% of the total precipitation (271.75 million m3/y or approximately 181.2 mm) infiltrated the groundwater aquifer, while the rest was lost by either surface runoff or evapotranspiration. Based on GRP sensitivity analysis index, lithology was the most efficient influencing factor in GRP mapping. Most groundwater wells (>96% or 369 wells) were classified into the classes of low and moderated, which agree to the GRP zones. The results of calculating the area under the curve (AUC) of the receiver operating characteristic (ROC) curve were 86.0 percent, with relatively good predictive accuracy. The stable baseflow analysis would be used to confirm the amount of GRP by weighting overlay technique. Therefore, the GRP method can be applied in other areas, particular in similar hydrogeological characteristics. The first-hand recharge potential map and groundwater recharge information in this area can be used to establish an effective groundwater exploration program for agricultural activities; it is also used to appropriate sustainable yields from each groundwater basin to provide groundwater over the long-term, without negatively impacting the environment and without affecting the groundwater balance as it has recharge in the rainy seasons, which can use groundwater sustainably. It is in line with the sustainable development goals (SDGs) in goal number six of the UN.

ANALISIS KESESUAIAN LAHAN DI KAWASAN HUTAN DENGAN TUJUAN KHUSUS (KHDTK) BULUH CINA, RIAU

Forest Area with Special Purposes (KHDTK) Buluh Cina requires a land suitability analysis so that the development of plant species can be carried out optimally. This study aims to map land units and determine land suitability classes. This study uses aerial photography to classify land cover and take soil samples. Furthermore, overlay analysis and species matching were carried out for 7 types of plants including durian, rambutan, sengon, mango, cacao, pineapple, and corn. The land suitability class is divided into 4 levels namely, very suitable (S1), suitable (S2), marginally suitable (S3), and not suitable (N). Based on the results, the actual land suitability class at KHDTK Buluh Cina class S1 was rambutan at SPL I and III. Land suitability class S2 is rambutan at SPL II and IV. S3 land suitability classes are durian, sengon, mango, cocoa, pineapple, and corn in SPL I, II, III, and IV. The potential land suitability class at KHDTK Buluh Cina class S1 is rambutan at SPL I, II, III and IV. Land suitability class S2 is durian, sengon, and cocoa at SPL I, II, III, and IV. S3 land suitability class is mango, pineapple, and corn in SPL I, II, III, and IV.

Assessment of the role of physicochemical properties of the soil on the formation of badlands around Chitrakoot, India

The present paper attempts to study the causative physicochemical properties of the soils, which effectively portray its dispersive and deteriorating conditions, which have led to the formation of badlands in the Mandakini River watershed Chitrakoot area, India. Following investigations were made on the soil samples collected from the field: i) grain size distribution ii) various physicochemical properties and nutrient content of the soil. The clay minerals were detected and identified with the X-ray diffraction (XRD), Fourier transform infrared (FTIR), and High-Resolution Scanning Electron Microscopy (HRSEM). The spatial maps of all these parameters were prepared in a GIS environment, and overlay analysis was performed. The results show that the soil has a silt loam texture with high bulk density. The low values of plastic limit, liquid limit, and plasticity index show the non-cohesive nature of the soils. Higher bulk density has decreased the porosity as well as permeability in the soils. This impact on porosity and permeability has reduced the favourable conditions for vegetation, and the soils contain low organic matter. Apart from the bulk density, the presence of calcrete and illitic clay mineral (low in content) has also reduced the permeability of the soils, further increasing runoff. The overlay analysis based on the liquid limit, plasticity index, bulk density, and drainage frequency shows that the area is thoroughly affected by badland processes. Three zones were categorized as severe, very severe, and extremely severe depending upon their conditions gully channel processes.

Modelling urban mixed land-use prediction using influence parameters

Mixed land-use is a popular concept in urban planning due to its expected role in improving environmental sustainability as well as citizen’s quality of life. Land use planning and regulations are not stringent in many cities like those in India, and policies are liberal towards mixed land uses. In these cities, mixed land-uses are a natural phenomenon manifesting under various influencing parameters. However, for studies on mixed land-uses, these cities pose data insufficiency challenges, as vital comprehensive spatial information related to land-uses is not available. Moreover, there is no standardised methodology established to assess the spatial distribution of mixed land-uses at the city level. This research has developed a GIS-based model using Weighted Overlay Analysis to predict and visualise the probability of mixed land-use at the macro or city level for the case of Pune, India. The model uses the easily available spatial data of influencing parameters of mixed land-use as input for prediction instead of comprehensive real land-use data. The model is validated by comparing the predicted mixed land-use intensities with established indicators of mixed land-use for four neighbourhoods. It is found that parameters that influence mixed land-use such as connectivity, grain pattern, population density and access to amenities can be used to predict the probability of mixed land-use. Around 35 per cent of the city area of Pune has more than 0.67 probability of mixed land-use. The model can produce the probable mixed land-use distribution across the city and can be used to compute mixed land-use intensities for neighbourhoods. Highlights for public administration, management and planning: • Mixed land-use probability distribution for Pune City, India is generated using Weighted Overlay Analysis in GIS. • As vital spatial data of land-use was unavailable, the prediction model uses data of influencing parameters of mixed land-uses such as population density, connectivity, grain pattern and access to amenities. • The mixed land-use probabilities predicted can be used to compute mixed land-use intensities of neighbourhoods. It is validated by comparing with traditional mixed land-use indicators.

A Multi-Criteria Index For Wetland Reconstruction Site Suitability In Ontario's Mixedwood Plains

Significant wetland loss in Ontario has resulted in the loss of important ecosystem services which help to mitigate the effects of global change. This research aimed to create a multi-criteria index for identifying where suitable sites for wetland reconstruction are spatially distributed in Ontario’s Mixedwood Plains. The index is intended as a decision-making tool for reaching wetland reconstruction goals such as those outlined by the Ontario MNRF’s plan to restore historically lost wetland area and function. By incorporating ecosystem services, the index will indicate areas where wetlands would be most beneficial. The resulting index generated a raster with a range of suitability based on seven criteria. Soil drainage and Agriculture were the most important criteria and weighed most heavily in the index. Overlay analysis indicated that suitable sites were clustered in areas which had historically undergone wetland loss or are areas of existing wetlands.