Holistic assessment of India's water security using coupled climate-human intervention models.

Climate change impacts on water security in global drylands

The development and evolution of an urban green space system is affected by both natural effects and human intervention. The simulation and prediction of an urban green space system can enhance the foresight of urban planning. In this study, several land use change scenarios of the main urban area of Xuchang City were simulated from 2014 to 2030 based on high-resolution land use data. The layout of each scenario was evaluated using landscape indexes. A Cellular Automata–based method (i.e., future land use simulation, FLUS) was applied to develop the urban green space system, which we combined with urban land use evolution. Using recent data, the FLUS model effectively dealt with the uncertainty and complexity of various land use types under natural and human effects and solved the dependence and error transmission of multiperiod data in the traditional land use simulation process. The root mean square error (RMSE) of probability of the suitability occurrence module and the Kappa coefficient of the overall model simulation accuracy verification index both met accuracy requirements. It was feasible to combine the evolution of the urban green space system with urban land development. Moreover, under the Baseline Scenario, the urban land use layout was relatively scattered, and the urban green space system showed a disordered development trend. The Master Plan Scenario had a compact urban land use layout, and the green space system was characterized by networking and systematization, but it did not consider the service capacity of the green space. The Planning Guidance Scenario introduced constraint conditions (i.e., a spatial development strategy, green space accessibility, and ecological sensitivity), which provided a more intensive and efficient urban space and improved the service function of the green space system layout. Managers and planners can evaluate the urban future land use development mode under different constraints. Moreover, they would be able to adjust the urban planning in the implementation process. This work has transformed the technical nature of the planning work from “static results” to a “dynamic process”.

The Greater Mekong Subregion (GMS) has experienced rapid economic growth and urbanization. However, few studies have paid attention to urban land use dynamics, especially spatiotemporal patterns of urban expansion and land use change, in this region. This research aimed to conduct a comprehensive study of urban land use change in Xishuangbanna, Yangon, Vientiane, Phnom Penh, Bangkok, and Ho Chi Minh City, from 1990 to 2015. The analysis was based on land use maps derived from Landsat satellite products and employed urban expansion intensity, sector analysis, gradient-direction analysis, and landscape metrics. The results show Xishuangbanna, Yangon, Vientiane, Phnom Penh, Bangkok, and Ho Chi Minh City all experienced dramatic urban expansion and land use change since 1990, with urban expansion intensities of 15.01, 5.26, 9.15, 1.56, 11.88 and 11.91, respectively. The landscape metrics analysis indicated that urban areas were always aggregated and self-connected, while other land use types showed trends of disaggregation and fragmentation. In the process of urban expansion, paddy and natural land use types were commonly transformed to built up area. The results further reveal several common issues in urban land use, e.g., land fragmentation and loss of natural land use types. Finally, the discussion on the relationship between government policy and land use change for these cities shows land reform and attitude toward foreign direct investments played important roles in urban land use change in GMS.

Analyzing the spatiotemporal evolution of urban land use and habitat quality can reveal the correlation between land use and habitat quality, aiding in rational urban land policies and high-quality ecological environment development. This study was based on land use transition matrices and an Intensity-Migration （IM） model to analyze the changes in land use in Harbin from 2000 to 2020. It combined the PLUS model to explore the driving factors of land use expansion for various land types and predicted land use scenarios for 2030 under natural development, ecological protection, farmland protection, and urban development scenarios. Finally, the InVEST model was used to complete the habitat quality analysis. The results indicated： ① The dominant land use types in Harbin were cropland, forest land, and grassland. From 2000 to 2020, there was a significant tendency of conversion into grassland, cropland, forest land, and artificial surfaces, with noticeable changes in land use intensity. Water bodies, bare land, and wetland types showed less conversion and tended to be restrictive. ② Elevation was the primary factor influencing the expansion of grassland, cropland, forest land, bare land, wetland, and water bodies. Socioeconomic factors were the main factor affecting the expansion of artificial surfaces. ③ Simulation of land use types in Harbin for 2030 under the four scenarios showed an increase in forest land area and a decrease in grassland area, with insignificant changes in wetland, water bodies, and bare land areas. Except for in the ecological protection scenario, the area of artificial surfaces increased, whereas cropland decreased. ④ Overall, habitat quality in Harbin improved from 2000 to 2020. ⑤ In 2030, the spatial pattern of habitat quality in Harbin remained consistent across all scenarios, showing an overall improvement in habitat quality. Under the ecological protection scenario, areas with low and medium habitat quality decreased, whereas areas with higher habitat quality increased, indicating a relatively significant improvement in habitat quality. The research results provide a scientific basis and insights for the development of ecological civilization and urban planning and construction in Harbin.

Extended Abstract 1.Introduction Today the role and the importance of open and green spaces are significantly increasing in the environment and the quality of building complex. Therefore, open and green spaces are considered as intrinsic, parts of land use planning decision in most countries. The gardens in the city of Jahrom are the indexes of Iranian thought and creativity and also the climatic consistency. Urban garden should be planned in green lands and some particular situations such as the arid climate. It should be mentioned that urban gardens are important in these conditions. In recent years, these gardens were destructed due of different causes along with the lack of plan. Therefore, human settlements and irregular buildings were replaced by green spaces or gardens. Gradually, these gardens were subjected to destruction risk. In this field, the main study questions include: 1) What are the most important causes of land use change in the gardens of the city of Jahrom; 2) What is the role of urban management in the land use change of gardens? 2. Theoretical Framework In urban management of all organizations, organizations and individuals are said to affect the process of city management either formally or informally. One of the most important factors contributing to the preservation of green space (gardens) and the prevention of any changes in the region is how to manage these experiences. The purpose of urban land use change is to change the plans approved by the city, including the plans within the framework of the comprehensive plan and the city services. The discovery and identification of changes in urban land use planning is one of the most important issues and requirements of urban management. In this sense, the issues of regulation and urban planning, organization and social justice in terms of equality and inequality in the distribution and value-added taxes in the city are important. The awareness of this clash of economic interests as opposed to natural resources makes reviewing and modifying the content and the enforcement of laws inevitable. In legal terminology, the change of application is defined as having permission to use the land in a way different from what is predicted in the approved city plans. The change of application is due to the request of the owner, municipal declaration, and the approval of article 5 of the Supreme Council of Architecture and Urban Planning Commission. In this situation, ownership and domination are outstanding. But sometimes the change is done without informing the owner. 3. Methodology The method used in the study is descriptive–analytical; it is of applied-developmental approach. This study has tried to investigate the effective cause of land use change in the gardens of the city of Jahrom by emphasizing the role of urban management. In this field, needed data has been collected through library data and survey studies (questionnaire and observation). Excel and GIS software have been used to analyze the collected data through the questionnaire. The population of this study consist of studying garden land use change files for purposes of observing legal framework in Article 5 commission in the municipality of Jahrom. The numbers of 36 plots of gardens have been investigated that have changed land use during 1996 -2010 (by Article 5 commission and field yield) It should be mentioned that during these years, all of changed land use gardens were 21 gardens in Article 5 commission of municipality of Jahrom and 15 gardens changed land use by field yield operations and interview with yield owner. These gardens have changed land use informally and in all owner agreement with municipality. 4. Results& Discussion The effective factors in the land use change of gardens in the city of Jahrom can be divided into two sets of general and special factors: 1. General factors These factors include all of gardens and are not just for a special part of gardens. 2. Special factors The effective factors in the land use change of gardens in the city of Jahrom and their change rates during years of 1996-2010 indicate that 190 hectares of these gardens have changed their land use to other urban land use during these years. About 5 hectares of these gardens have been lost due to the economic factors (mainly the land and house added value). The factors in question include 26.84% all land use changes of gardens during this statistical period. Therefore, it is safe to say that economic factors (mainly land and house added value) are considered the most important factors in the land use change of gardens in the city of Jahrom. 5. Conclusionsand Suggestions The findings of the study indicate that effective factors in the land use change of gardens in the city of Jahrom are of two kinds: general and special. During the years of 1996-2010, about 190 hectares of gardens changed their land use to other urban land use. Economic factors are considered the most important causes of the land use change of gardens in the city of Jahrom. Mostly the land use change of gardens and green spaces are related to the residential use (88.9%). It is safe to conslude that the regulations of Article 5 Commission and the agreement of owner and municipality in the domain of the land use changes of green spaces have resulted in the residential land use significantly. Therefore, the performance of the municipality of Jahrom with respect to the Article 5 Commission has not been successful in preserving green space (gardens). Finally, to avoid this change of use, it is proposed to use barren lands within the city for the urban infrastructure development to maintain gardens in line with sustainable development.

Urbanization and its effects on water resources: Scenario of a tropical river basin in South India

Natural landscapes have changed significantly through anthropogenic activities, particularly in areas that are severely impacted by climate change and population expansion, such as countries in Southeast Asia. It is essential for sustainable development, particularly efficient water management practices, to know about the impact of land use and land cover (LULC) changes. Geographic information systems (GIS) and remote sensing were used for monitoring land use changes, whereas artificial neural network cellular automata (ANN-CA) modeling using quantum geographic information systems (QGIS) was performed for prediction of LULC changes. This study investigated the changes in LULC in the Perak River basin for the years 2000, 2010, and 2020. The study also provides predictions of future changes for the years 2030, 2040, and 2050. Landsat satellite images were utilized to monitor the land use changes. For the classification of Landsat images, maximum-likelihood supervised classification was implemented. The broad classification defines four main classes in the study area, including (i) waterbodies, (ii) agricultural lands, (iii) barren and urban lands, and (iv) dense forests. The outcomes revealed a considerable reduction in dense forests from the year 2000 to 2020, whereas a substantial increase in barren lands (up to 547.39 km2) had occurred by the year 2020, while urban land use has seen a rapid rise. The kappa coefficient was used to assess the validity of classified images, with an overall kappa coefficient of 0.86, 0.88, and 0.91 for the years 2000, 2010, and 2020, respectively. In addition, ANN-CA simulation results predicted that barren and urban lands will expand in the future at the expense of other classes in the years 2030, 2040, and 2050. However, a considerable decrease will occur in the area of dense forests in the simulated years. The study successfully presents LULC changes and future predictions highlighting significant pattern of land use change in the Perak River basin. This information could be helpful for land use administration and future planning in the region.

China’s urban land use has shifted from incremental expansion to inventory eradication. The traditional extensive management mode is difficult to maintain, and the fundamental solution is to improve land use efficiency. Xi’an, the largest central city in Western China, was selected as the research area. The super-efficiency data envelopment analysis (DEA) model and Malmquist index method were used to measure the land use efficiency of each district and county in the city from the micro perspective, and the spatial-temporal change characteristics and main influencing factors of land use efficiency were analyzed, which not only made up for the research content of urban land use efficiency in China’s underdeveloped areas, but also pointed out the emphasis and direction for the improvement of urban land use efficiency. The results showed that: (1) The land use efficiency of Xi’an reflected the land use intensive level of the underdeveloped areas in Western China, that is, the overall intensive level was not high, the gap between the urban internal land use efficiency was large, the land use efficiency of the old urban area and the mature built-up area was relatively high, and the land use efficiency of the emerging expansion area and the edge area was relatively low. (2) Like the eastern economically developed areas, the land use efficiency of western economically underdeveloped areas was generally on the rise, while Xi’an showed the U-shaped upward evolution characteristics, and there were four types of changes in the city, that is, highly intensive, medium intensive, high–medium–low-intensive, and intensive–extensive. (3) Various cities should configure resources and optimize mechanism to improve their land use efficiency based on economic and social development. During the study period, Xi’an showed the law of evolution from the south edge area and the emerging expansion area to the main urban area. (4) The improvement of technological progress was the main contribution factor of the land use efficiency in underdeveloped areas of China, and the low-scale efficiency was the main influence factor that caused low land use efficiency. In future urban land use, efforts should be made to optimize and upgrade technology and strictly control the extensive use of land.

The extent of anthropogenic land use in watersheds determines the amount of pollutants discharged to streams. This indirectly and directly affects stream water quality and biological health. Most studies have therefore focused on ways to reduce non-point pollution sources to streams from the surrounding land use in watersheds. However, the mechanistic pathways between land use and the deterioration of stream water quality and biological assemblages remain unclear. This study estimated a structural equation model (SEM) representing the impact of agricultural and urban land use on water quality and the benthic macroinvertebrate index (BMI) using IBM AMOS in the Nam-Han river systems, South Korea. The estimated SEM showed that the percent of urban and agricultural land in the watersheds significantly affected both the water quality and the BMI of the streams. Specifically, a higher percent of urban land use had directly increased the biochemical oxygen demand (BOD) and total phosphorus (TP), and deteriorated the BMI of streams. Similarly, higher proportions of agricultural land use had also directly increased the BOD, total nitrogen (TN), and total phosphorus (TP) concentrations, and lowered the BMI of streams. In addition, it was observed that the percent of urban and agricultural land use had indirectly deteriorated the BMI through increased BOD. However, we were not able to observe any significant indirect effect of the percent of urban and agricultural land use through increased nutrients including TN and TP. These results indicate that increased urban and agricultural land use in the watersheds had directly and indirectly affected the physicochemical characteristics and benthic macroinvertebrate communities in streams. Our findings emphasize the need to develop more elaborate environmental management and restoration strategies to improve the water quality and biological status of streams.

Abstract. How will the combined impacts of land use change, climate change, and hydrologic modeling influence changes in urban flood frequency and what is the main uncertainty source of the results? Will such changes differ by catchment with different degrees of current and future urban development? We attempt to answer these questions in two catchments with different degrees of urbanization, the Fanno catchment with 84% urban land use and the Johnson catchment with 36% urban land use, both located in the Pacific Northwest of the US. Five uncertainty sources – general circulation model (GCM) structures, future greenhouse gas (GHG) emission scenarios, land use change scenarios, natural variability, and hydrologic model parameters – are considered to compare the relative source of uncertainty in flood frequency projections. Two land use change scenarios, conservation and development, representing possible future land use changes are used for analysis. Results show the highest increase in flood frequency under the combination of medium high GHG emission (A1B) and development scenarios, and the lowest increase under the combination of low GHG emission (B1) and conservation scenarios. Although the combined impact is more significant to flood frequency change than individual scenarios, it does not linearly increase flood frequency. Changes in flood frequency are more sensitive to climate change than land use change in the two catchments for 2050s (2040–2069). Shorter term flood frequency change, 2 and 5 year floods, is highly affected by GCM structure, while longer term flood frequency change above 25 year floods is dominated by natural variability. Projected flood frequency changes more significantly in Johnson creek than Fanno creek. This result indicates that, under expected climate change conditions, adaptive urban planning based on the conservation scenario could be more effective in less developed Johnson catchment than in the already developed Fanno catchment.

Based on the theories of the information entropy of urban land use structure, co-integration and error correction model, this thesis analyses the relationship between economic growth, urbanization level and the information entropy of urban land use structure. The information entropy values of China's urban land use structure from 1981 to 2004 have been calculated in this paper. The relationship between China's GDP and the information entropy of urban land use structure is investigated in details. The results indicate a co-integration relationship between GDP and the information entropy of urban land use structure. However, there is no co-integration relationship between urbanization and the information entropy of urban land use structure. On the basis of the above analyses, the error correction model on GDP and the information entropy of urban land use structure is instituted. The application of the model shows that every 1% decrease in the information entropy value of urban land use structure demands a 59.53% growth in GDP. Because of the existing co-integration relationship between the economic growth and the information entropy of urban land use structure, the order degree of China's urban land use structure has relied heavily on the economic growth for a long time. The economic growth will significantly affect the optimal regulation of urban land use structure in the future. Further investigation also shows that economic growth and urbanization act as the direct driving force of the optimization of urban land use structure, but the optimization of urban land use structure can't promote the economic growth and the urbanization. Therefore, it becomes a very pressing strategic issue to adjust the economic structure and industrial distribution to optimize the distribution of urban land use and to optimize the structure of urban land use to improve the efficiency and promote the socio-economic development.

Impact of land use compactness on the habitat services from green infrastructure in Wuhan, China

Spatio-temporal variation and prediction of land use based on CA-Markov of southwestern coastal district of Bangladesh

Water insecurity, driven by urbanization, population growth, land use and climate change, poses a global challenge. This study examines water supply and demand trends in the Mbagathi-Stony Athi sub-catchments, highlighting urbanization's impact in a semi-arid context. Using GIS, and the WEAP model, various scenarios were simulated. Results show annual rainfall increased insignificantly (p = 0.61) from 1981 to 2019. By 2063, rainfall is projected to rise by 12.43% (RCP 4.5) and 21.02% (RCP 8.5). Mean temperature increased by 0.88 °C (1981–2019) and is projected to rise by 1.70 °C (RCP 4.5) and 1.75 °C (RCP 8.5) by 2063. Land use analysis (2000–2019) showed a 53.67% increase in built-up areas and a 99.32% decline in wetlands. Between 2000 and 2019, the annual supply, demand, and unmet demand increased by 171.64%, 147.56%, and 73%, respectively. Land use changes between 2000 and 2019, particularly the increase in shrublands and decline in bare land, contributed to a 25.51% decrease in surface runoff and a 3.55% rise in total annual evapotranspiration. Future projections indicate surface runoff decreases of up to 4.47% under RCP 4.5 and increases of 9.38% under RCP 8.5. Potential evapotranspiration is projected to rise by 23.39% (reference), 16.44% (RCP 4.5), and 11.19% (RCP 8.5). Water demand will increase across all scenarios, peaking at 184% under high urbanization, while unmet demand will rise by up to 162.47% under irrigation expansion. Water scarcity is expected to worsen due to climate change, population growth, and land use shifts. These findings inform sustainable water resource management in development corridors.

Detecting Land use and land cover change and vegetation condition has become a central component in current strategies for managing and monitoring of environmental changes caused by anthropogenic activities. To come up with such decisions, geoinformatics technology is providing new tools to conduct vegetation and land use land cover change detection analysis for managing and wise utilisation of natural resources as well as to provide information for policymakers in a given study area. This study examines the use of geoinformatics technology to analyse land use land cover (LULC) change and vegetation dynamics using multi-temporal satellite images for the maryamdehan kebele in the years 1984, 2005 and 2015. Both primary and secondary data were used from different sources. Satellite images of the year 1984, 2005 and 2015 were downloaded from the govis.usgs.gov website and ground control points (GCP) data were collected by handheld GPS for supervised image classification in Erdas imagine and ArcGIS environment. The findings show that six main land use land cover classes were detected and vegetation values were also computed in each period. As a result, the total area of the kebele was 3646.49 hectare, from which in 1984 forest area (40.691%), grassland (26.15%) and farmland (10.81%) were dominant classes and in 2005 settlement (52.41%), forest area (25.04%) & farmland (11.71%) and in 2015, 35.14% was covered by forest land, 30.04% by Settlement, and 14.74% by farmland. Water resource decreases from 9.3% to 0.64% in 2015 and the bare land also changes from 3.18% to 0.903% because of urban expansion and agricultural activities in the kebele. In addition, the vegetation condition looks like a sinusoidal trend from the year 1984 up to 2015 because of climate change and human interventions in the kebele. To conclude that detecting LULC change and analysis of vegetation dynamics plays a great role in land use management and wise utilisation of natural resources by applying Geoinformatics tools in the kebele and it provides information for the policymakers to prepared future plan and for sustainable development.