Land Use And Land Cover Scenarios Research Articles

The impacts of LULC and climate change scenarios on the hydrology and sediment yield of Rib watershed, Ethiopia.

Watershed-scale hydrology and soil erosion are the main environmental components that are greatly affected by environmental perturbations such as climate and land use and land cover (LULC) changes. The purpose of this study is to assess the impacts of scenario-based LULC change and climate change on hydrology and sediment at the watershed scale in Rib watershed, Ethiopia, using the empirical land-use change model, dynamic conversion of land use and its effects (Dyna-CLUE), and soil and water assessment tool (SWAT). Regional climate model (RCM) with Special Report on Emission Scenarios (SRES) and Representative Concentration Pathway (RCP) outputs were bias-corrected and future climate from 2025 to 2099 was analyzed to assess climate changes. Analysis of the LULC change indicated that there has been a high increase in cultivated land at the expense of mixed forest and shrublands and a low and gradual increase in plantation and urban lands in the historical periods (1984-2016) and in the predictions (2016-2049). In general, the predicted climate change indicated that there will be a decrease in precipitation in all of the SRES and RCP scenarios except in the Bega (dry) season and an increase in temperature in all of the scenarios. The impact analysis indicated that there might be an increase in runoff, evapotranspiration (ET), sediment yield, and a decrease in lateral flow, groundwater flow, and water yield. The changing climate and LULC result in an increase in soil erosion and changes in surface and groundwater flow, which might have an impact on reducing crop yield, the main source of livelihood in the area. Therefore, short- and long-term watershed-scale resource management activities have to be designed and implemented to minimize erosion and increase groundwater recharge.

Investigating Relationships between Runoff–Erosion Processes and Land Use and Land Cover Using Remote Sensing Multiple Gridded Datasets

Climate variability, land use and land cover changes (LULCC) have a considerable impact on runoff–erosion processes. This study analyzed the relationships between climate variability and spatiotemporal LULCC on runoff–erosion processes in different scenarios of land use and land cover (LULC) for the Almas River basin, located in the Cerrado biome in Brazil. Landsat images from 1991, 2006, and 2017 were used to analyze changes and the LULC scenarios. Two simulations based on the Soil and Water Assessment Tool (SWAT) were compared: (1) default application using the standard model database (SWATd), and (2) application using remote sensing multiple gridded datasets (albedo and leaf area index) downloaded using the Google Earth Engine (SWATrs). In addition, the SWAT model was applied to analyze the impacts of streamflow and erosion in two hypothetical scenarios of LULC. The first scenario was the optimistic scenario (OS), which represents the sustainable use and preservation of natural vegetation, emphasizing the recovery of permanent preservation areas close to watercourses, hilltops, and mountains, based on the Brazilian forest code. The second scenario was the pessimistic scenario (PS), which presents increased deforestation and expansion of farming activities. The results of the LULC changes show that between 1991 and 2017, the area occupied by agriculture and livestock increased by 75.38%. These results confirmed an increase in the sugarcane plantation and the number of cattle in the basin. The SWAT results showed that the difference between the simulated streamflow for the PS was 26.42%, compared with the OS. The sediment yield average estimation in the PS was 0.035 ton/ha/year, whereas in the OS, it was 0.025 ton/ha/year (i.e., a decrease of 21.88%). The results demonstrated that the basin has a greater predisposition for increased streamflow and sediment yield due to the LULC changes. In addition, measures to contain the increase in agriculture should be analyzed by regional managers to reduce soil erosion in this biome.

Modeling of Land Use and Land Cover (LULC) Change Based on Artificial Neural Networks for the Chapecó River Ecological Corridor, Santa Catarina/Brazil

The simulation and analysis of future land use and land cover—LULC scenarios using artificial neural networks (ANN)—has been applied in the last 25 years, producing information for environmental and territorial policy making and implementation. LULC changes have impacts on many levels, e.g., climate change, biodiversity and ecosystem services, soil quality, which, in turn, have implications for the landscape. Therefore, it is fundamental that planning is informed by scientific evidence. The objective of this work was to develop a geographic model to identify the main patterns of LULC transitions between the years 2000 and 2018, to simulate a baseline scenario for the year 2036, and to assess the effectiveness of the Chapecó River ecological corridor (an area created by State Decree No. 2.957/2010), regarding the recovery and conservation of forest remnants and natural fields. The results indicate that the forest remnants have tended to recover their area, systematically replacing silviculture areas. However, natural fields (grassland) are expected to disappear in the near future if proper measures are not taken to protect this ecosystem. If the current agricultural advance pattern is maintained, only 0.5% of natural fields will remain in the ecological corridor by 2036. This LULC trend exposes the low effectiveness of the ecological corridor (EC) in protecting and restoring this vital ecosystem.

A data-driven machine learning-based approach for urban land cover change modeling: A case of Khulna City Corporation area

Land use and land cover (LULC) changes have significant consequences on habitat and the environment. Past studies developed several LULC change models to identify the factors behind the changes and to simulate future LULC scenarios. However, the accuracy of these models remained contentious and a matter of ongoing debate and research. Most of these studies used a training dataset to train the model and a validation dataset to validate the prediction accuracy, both of which are a part of the original training dataset. However, to evaluate the model's actual predictive capability in terms of spatial data modeling, it is necessary to test the model's performance on the real-world dataset. In this study, we presented an XGBoost model aiming at improving the prediction accuracy while used a separate test dataset to test the model's actual predictive capacity. We applied the method to predict the land cover change of the Khulna City Corporation (KCC) area in Bangladesh. The study reveals that the KCC area experienced rapid urban development during the 2002–2018 period while the agricultural and vacant land declined at a similar rate. The major factors contributing to this substantial change of the city's land covers are-proximity to existing built-up areas and proximity to major roads. Our study indicates that agricultural areas and wetlands closer to the major roads and existing urban areas have a greater probability of converting into built-up areas. Our experiment demonstrates that the XGBoost model can predict the city's land cover change with greater accuracy and outperforms the benchmark models such as the LR-CA and ANN-CA. The finding assures the reliability of the XGBoost model while predicting future land-cover scenarios.

Enhancing LULC scenarios impact assessment in hydrological dynamics using participatory mapping protocols in semiarid regions

Land use and land cover (LULC) scenarios in rural catchment hydrology are crucial to describe the effects of future water dynamics. However, there is a lack of understanding of the effectiveness of including static land covers at the subbasin level to provide inter-annual stability in changing the different water balance components. We developed a step-by-step mapping protocol to extend and enrich the hydrological assessment of future LULC scenarios defined through participatory stakeholder involvement. This novelty included specific allocation of static and dynamic LULC change among the scenarios and then compared the change of water dynamics to the current situation. For this, we quantified the LULC impact on the components of the water balance from three contrasting participatory scenarios implemented with the SWAT model in a rural basin in central Spain. The Land-sharing scenario (LSH) had the highest percentage of permanent grassland and shrubs and no increase of irrigated land compared to baseline. The land-sparing scenario (LSP) intensified agricultural land use close to urban areas, and the land balance scenario (LBA) was intermediate. The LSH increased the aquifer recharge by +1.7% and streamflow by +1.5%, while evapotranspiration and soil water storage decreased by -0.2%. In contrast, the LBA decreased in the riverine flux of -0.5%, an aquifer recharge of -0.6%, a soil water storage of -3.5%, and an evapotranspiration rate of +0.3%. Thus, LSH revealed that the allocation of permanent land cover such as grassland could buffer water dynamics, suggesting that dedicated planning and allocation of permanently vegetated LULC will favour land and water conservation.

Analysis of the response of the Epitácio Pessoa reservoir (Brazilian semiarid region) to potential future drought, water transfer and LULC scenarios

The Brazilian semiarid region (BSAR) is affected by the high precipitation variability and severe drought events over time, promoting recurrent water scarcity. The water supply in the BSAR has suffered since 2012 from severe incidents of rainfall reduction, creating a complex scenario of water scarcity, for instance, in Campina Grande city, which is supplied by the Epitacio Pessoa reservoir (EPR). This study analyzed the future impacts on the volume of the EPR based on potential future droughts, water transfer from the Sao Francisco River, population growth and recent changes in land use and land cover (LULC). Several procedures were performed, including (a) simulation of LULC scenarios with the LCM algorithm, (b) simulation of future rainfall scenarios for the period from 2020 to 2030, (c) streamflow simulation using the Soil Water and Assessment Tool (SWAT) model and (d) prediction of water storage in the EPR for the period from 2020 to 2030 using three rainfall scenarios (− 40%, − 45% and − 50%). The results indicated that the SWAT calibration and validation results were considered satisfactory based on the R2, Nash, and PBIAS values. The results were assumed from the rainfall scenarios for the period from 2020 to 2030 together with the LULC scenario for 2030, including the estimated outflow of water transfer from the Sao Francisco River. The results showed, based on the three adopted rainfall scenarios, that the reservoir would reach its critical volume in the first two years of the analyzed period, and the reservoir volume would then increase until 2024 and subsequently return to decrease, reaching the critical volume in 2030.

Modeling the impacts of future LULC and climate change on runoff and sediment yield in a strategic basin in the Caatinga/Atlantic forest ecotone of Brazil

Water management in the Caatinga/Atlantic forest ecotone in Brazil is critically dependent on better understanding of potential future changes in streamflow and sediment dynamics. This paper evaluates both the future impacts of land use and land cover (LULC) changes and the impacts of climate change on the streamflow and sediment yield in the Tapacurá River basin in northeastern Brazil, using a novel combination of approaches. Projected climate data derived using global circulation model HadGEM2-ES were coupled to regional circulation model ETA-CPTEC/HadCM3 for two representative concentration pathways (RCP 4.5 and 8.5), with bias correction. Two future LULC scenarios were generated: (a) optimistic (current LULC), and (b) pessimistic (land use change trends continue), using the multilayer perceptron algorithm (MP). The Soil and Water Assessment Tool (SWAT) model was used to estimate future streamflow and erosion for different periods (2011–2040, 2041–2070 and 2071–2099). The SWAT model was calibrated for period of 1995–2003 and validated for 2004–2013. The results showed good accuracy in relation to R2, NSE and PBIAS for the calibration and validation of the runoff, as well as for the verification of the sediment yield. Simulations indicated significant increases in erosion for the pessimistic scenario under RCP 8.5, followed by the pessimistic scenario and RCP 4.5. Lower sediment yields occurred for the optimistic and RCP 8.5, with lower still for the optimistic and RCP 4.5. However, the latter estimates are still considerably higher than baseline conditions. Although higher flows are found for some scenarios, the increases in sediment yield have serious implications for reservoir siltation and storage reduction. Despite modeling uncertainty, the results demonstrate that the proposed methodology has promising scope to contextualize potentially significant regional hydrological changes which have implications for land and biodiversity management and the sustainability of water resources in the Caatinga/Atlantic forest ecotone.

Comprehensive assessment and scenario simulation for the future of the hydrological processes in Dez river basin, Iran

Abstract Climate change is one of the leading factors that directly affect hydrological processes in large basins. This study assesses the impacts of climate change on streamflow, sediment and crop yield, actual evapotranspiration (AET), and water budget. In addition, the effects of land use and land cover (LULC) alteration with climate change on streamflow and sediment yield have been evaluated in the Dez river basin in the southwest of Iran. Five General Circulation Models (GCMs) based on two scenarios, Representative Concentration Pathway (RCP) 4.5 and RCP 8.5 for the near period (2021–2040) are considered. Hydrological simulation is performed using the Soil and Water assessment tool (SWAT) with good performance in the calibration (1990 to 2010) and validation (2010 to 2017) periods. The precipitation and temperature projected show a major upward trend related to the base period. The results showed that climate change increases the runoff and sediments. In addition, results projected that garden crop yields would increase while agricultural crop yields would decrease. In addition, AET will face a slight decline of about 2%–6%. Combined LULC and climate change scenarios showed that with amplification of orchards areas, sediment load would decrease.

Disentangling the historic and future impacts of land use changes and climate variability on the hydrology of a mountain region in Brazil

Global changes in land use and land cover (LULC) and climate are expected to have profound impacts on water dynamics, which are key for human wellbeing. However, we still lack understanding of how changes in climate patterns and LULC are likely to interact and govern the hydrology at the watershed level in tropical regions in the future. Here we assessed the contribution of changes in weather patterns and LULC on the hydrology of a watershed in southeast of Brazil between 1990 and 2015 using the SWAT model. In addition, we explored the likely impacts of two contrasting LULC scenarios (Green Road versus Fossil Fuel) on the hydrology in 2045 under the Representative Concentration Pathway 8.5. Between 1990 and 2004 and 2005–2015 the watershed witnessed an increase in precipitation and streamflow, in combination with an expansion of forest cover and coffee production. While surface runoff (+5.2 mm year−1) and water yield (+252 mm year−1) increased, soil water (−24.6 mm year−1) and evapotranspiration (−15.7 mm year−1) decreased. The analysis indicated that changes in climate patterns are the main drivers of historical water dynamics in the region. Compared with Fossil Fuel scenario, the increase in forest area in the Green Road scenario will lead to a decrease in surface runoff and consequently in water yield, favouring water infiltration and soil erosion control, and buffer against extreme precipitation events. Therefore, the socioeconomic and public policies underlying the Green Road scenario that favour the expansion of forests can direct sustainable future water management.

Future scenarios based on a CA-Markov land use and land cover simulation model for a tropical humid basin in the Cerrado/Atlantic forest ecotone of Brazil

Recently, the advancement of agriculture in Brazil has caused very serious problems, such as deforestation and an increase in the amount of pesticides and suspended sediment that have negatively impacted the environment, especially in the Prata River basin, which is located in the Serra da Bodoquena region, Brazil. Thus, the objective of this study was to analyze the future changes in land use and land cover of the advancement of agriculture in the native vegetation areas of the Cerrado/Atlantic forest ecotone in the Prata River basin in 2033, 2050, 2080 and 2100. To map the future land use and land cover (LULC) in the study area, an object-based classification approach was used on Landsat satellite imagery from 1986, 1999, 2007 and 2016. The future LULC scenarios were created with a cellular automata-Markov forecast model. The simulation results of the LULC changes were considered satisfactory, as evidenced by the values obtained from the kappa for agreement (κstandard) = 0.73, kappa for no information (κno) = 0.79 and kappa for grid-cell level location (κlocation) = 0.85 indices. The modeled future scenarios of LULC indicated the advancement of crop agriculture and decreases in wetlands (banhado), savannahs, riparian forests, seasonal semideciduous forests and wet grasslands, which can be considered a warning about the loss of biodiversity of fauna and flora in the Serra da Bodoquena National Park, mainly in the Prata River basin.

Integrated assessment of land-use/land-cover dynamics on carbon storage services in the Loess Plateau of China from 1995 to 2050

Understanding the impacts of large-scale anthropogenic drivers on spatiotemporal processes in carbon storage through land-use patterns is a growing issue for the assessment of terrestrial ecosystems. However, an integrated assessment of changes in carbon storage, entailing complex land-use and land-cover (LULC) dynamics, remains a challenge. This study assessed the consequences of LULC changes on regional carbon storage in the Loess Plateau from 1995 to 2050 by integrating spatially explicit LULC and carbon models using multi-source data and typical scenarios. A Markov-CA model was used to model past LULC dynamics, which was followed by future projections under different LULC scenarios. Each scenario represented different socio-economic trajectories, including historical trend, ecological priority, and urban priority. The integrated valuation of the ecosystem service and tradeoffs (InVEST) carbon storage model and statistical methods were then used to assess spatiotemporal changes in the regional carbon storage associated with LULC dynamics. The results indicated that the ecological priority scenario could increase carbon storage by 11.36 Pg between 2015 and 2050. This is due to an increase in the carbon storage capacity in grasslands, shrub forest, and evergreen coniferous forest, indicating that ecological restoration could increase carbon sequestration. This mitigates the carbon loss caused by the rapid expansion of built-up land and fluctuations in cropland, which often takes place in the urban priority and historical trend scenarios. In favor of targeting the northwestern and central regions with socioeconomic benefits, grasslands and forests should be further promoted in the Loess Plateau. The findings will help implement long-term carbon sequestration strategies for ecosystem conservation.

Modeling of land-use and land-cover change impact on summertime near-surface temperature variability over the Delhi–Mumbai Industrial Corridor

This study explores the impact of land-use and land-cover (LULC) changes due to different urbanization scenarios in the Delhi–Mumbai Industrial Corridor (DMIC) region on surface air temperature by conducting sensitivity studies with the Weather Research and Forecasting (WRF) model. First, a sensitivity analysis conducted using the planetary boundary layer (PBL) and surface layer (SL) physical parameterizations available in WRF. Results show that the model performs better when a combination of the Mellor–Yamada–Janjic PBL and ETA SL schemes used. Then, numerical experiments performed using WRF with the above configuration and three different LULC scenarios to assess the possible impact of urbanization on near-surface temperature during May. A total of ten simulations were conducted for the May month of 2005–2014 to estimate the statistical and physical robustness of results. Each of these simulations considered as ensemble member while computing average values. The study shows that there is a significant effect of LULC change mainly on the minimum temperature (Tmin) with an increase of 2.9–3.7℃ over the DMIC region. The impact is less on maximum temperature, with a minor rise in 0.1–0.3℃. The probable reason for the increase in minimum temperature is likely due to a decrease in latent heat flux and an increase in sensible heat flux. The impact on air temperature was found to be prominent over existing urban clusters than the surrounding built environment; also, this effect is additive and more pronounced with the extreme LULC change scenario.

Land-Use and Land-Cover Change in Dhaka Eastern Region and Its Impact on Surface Run-off

The aim of this study is to identify the impending urbanization-led land-use and land-cover (LULC) change of Dhaka Eastern Region (DER) and assessing its impact on surface runoff. Remotely sensed image data and proposed land-use plans for DER is analyzed and mapped in this study to detect the changes of LULC. A faster pace of land transformation was observed during 2016-17 from unpaved to the paved surface. Four post-developed LULC scenarios were predicted from the classified Landsat imagery of 2016-17 with increasing imperviousness. Runoff was estimated by SCS-CN method integrating RS and GIS tools. LULC changes according to land cover classes were assimilated with the hydrologic soil groups and then runoff depths were estimated for annual rainfall events in DER. Like the slower trend of urbanization, area-weighted CN also increased slowly during 2016-17 but followed a moderate leap in RDP and scenario-1. However, CN dropped in scenario-2 mainly due to the change in land-cover by infilling of highly permeable hydrologic soils. Predicted scenario-3 and 4 resulted in higher CN respectively because of increasing imperviousness in LULC. Higher CN resulted in higher runoff and more drainage requirements. RDP scenario or the predicted scenario-1 with CN 84 is potentially a viable LULC option for DER by 2035 and beyond that may cause more than 30% to 50% runoff comparing to the representative 2010 LULC condition.

Land use and land cover scenarios: An interdisciplinary approach integrating local conditions and the global shared socioeconomic pathways

Land Use and Land Cover (LULC) changes have profound impacts on the functioning of (agro)ecosystems and have potential to mitigate global climate change. However, we still lack interdisciplinary methods to project future LULC scenarios at spatial scales that are relevant for local decision making and future environmental assessments. Here we apply an interdisciplinary approach to develop spatially explicit projections of LULC at a resolution of 30 × 30 m informed by historic relationships between LULC and their key drivers, within the context of the four qualitative scenarios of global shared socioeconomic pathways. We apply this methodology to a case study in the Zona da Mata, Brazil, which has a history of major LULC changes. The analysis of LULC changes from 1986 to 2015 indicates that pasture area decreased from 76 to 58 % of total area, while forest areas increased from 18 to 24 %, and coffee from 3 to 11 %. Environmental protection legislation, rural credit for smallholder farmers, and demand for agricultural and raw products were identified as main drivers of LULC changes. Projected LULC for 2045 strongly depends on the global socioeconomic pathway scenarios, and forest and coffee areas may increase substantially under strong government measures in the environmentally conscious Green Road scenario or decrease in the high consumption Rocky Road scenario. Our study shows that under the set of drivers during the past three decades reforestation can go hand in hand with increase of agricultural production, but that major and contrasting changes in LULC can be expected depending on the socioeconomic pathway that will be followed in the future. To guide this process, LULC scenarios at the local scale can inform the planning of local and regional development and forest conservation.

The Impact of Reforestation Induced Land Cover Change (1990–2017) on Flood Peak Discharge Using HEC-HMS Hydrological Model and Satellite Observations: A Study in Two Mountain Basins, China

Understanding the effect of land use and land cover (LULC) type change on watershed hydrological response is essential for adopting applicable measures to control floods. In China, the Grain to Green Program (GTGP) and the Natural Forest Conservation Program (NFCP) have had a substantial impact on LULC. We investigate the effect of these conservation efforts on flood peak discharge in two mountainous catchments. We used a series of Landsat images ranging from 1990 to 2016/2017 to evaluate the LULC changes. Further to this, the hydrological responses at the basin and sub-basin scale were generated by the Hydrologic Modeling System (HEC-HMS) under four LULC scenarios. Between 1990 and 2016/2017, both catchments experienced an increase in forest and urban land by 18% and 2% in Yanhe and by 16% and 8% in Guangyuan, respectively. In contrast, the agricultural land decreased by approximately 30% in Yanhe and 24% in Guangyuan, respectively. The changes in land cover resulted in decrease in flood peak discharge ranging from 14% in Yanhe to 6% in Guangyuan. These findings provide a better understanding on the impact of reforestation induced LULC change on spatial patterns of typical hydrological responses of mountainous catchment and could help to mitigate flash flood hazards in other mountainous regions.

Analysis of past and future multi-temporal land use and land cover changes in the semi-arid Upper-Mzingwane sub-catchment in the Matabeleland south province of Zimbabwe

ABSTRACT In this study, we analyse past spatio-temporal land use and land cover (LULC) change dynamics in the Upper-Mzingwane sub-catchment (UMS) located in the semi-arid Matabeleland south region of Zimbabwe using Landsat 5 Thematic Mapper (L5-TM) and Landsat 8 Operational Land Imager (L8-OLI) imagery for the periods of 1989, 2004, 2013, and 2018. We also model plausible future LULC scenarios for UMS. We distinguished five LULC classes, i.e. water, bareland, dense woodland, shrubland, and grassland using a hybrid approach entailing image classification in R-software using the Random Forest (RF) and Support Vector Machine (SVM) algorithms. Accuracy assessment and Kappa statistics revealed better performance of the SVM hence its outputs were used in the change analysis (i.e. to quantify LULC transitions and trends statistically). We then utilized the TerrSet Land Change Modeller (LCM) (using the Markov Chain algorithm with Multi-Layer Perceptron) to model future LULC scenarios up to 2038 at 5-year intervals. Results revealed that the grass, shrub, and woody vegetation are predominant land covers covering 48.5%, 31.5%, and 18.8% in 1989 and 54.4%, 28.8%, and 15.8%, respectively, in 2018. Dense woodland cover was projected to experience the greatest net loss of 43.57% while shrubland, grassland, water, and bareland increase by 10.73%, 4.5%, 26.85%, and 15.09%, respectively, between 2023 and 2038. We concluded that the UMS has since 1989, been losing and will continue to lose dense woodland cover into the future possibly due to increased human activities such as small scale and illegal gold mining in the area. As such, immediate remedial action needs to be taken to reverse the observed and possible future negative LULC change trends especially for woodland cover so as to avert likely adverse socio-economic, hydrological, and ecological consequences within and beyond the UMS.

Multi-Layer Perceptron Neural Network and Markov Chain Based Geospatial Analysis of Land Use and Land Cover Change

We combined multi-layer perceptron (MLP) neural network and Markov Chain (MC) modeling with object-based image analysis (OBIA) to map and predict land use and land cover (LULC) changes in Stoney Creek Watershed (SCW), British Columbia, Canada. Unsupervised classification was performed using Landsat Thematic Mapper (TM) and Operational Land Imager (OLI) images to produce LULC maps of years 1986, 1999 and 2016. The classification resulted in an overall accuracy of 91.50%. The results show that coniferous forest in SCW experienced a sharp loss while agriculture area increased (4.77% land gain) from 1986 to 2016. LULC scenarios were predicted through MLP neural network and MC modeling based on LULC change analysis data and transition potential. The results indicated that ‘Coniferous Forest’ LULC type had the highest (3.38% land loss) transition potential and ‘Water’ and ‘Urban Area’ LULC types had the lowest transition potential. Application of the proposed method provided valuable information of LULC patterns and dynamics for planners and researchers. The method also has the potential for improved management in other watersheds with similar LULC types.

Modeling the effect of land use and climate change on water resources and soil erosion in a tropical West African catch-ment (Dano, Burkina Faso) using SHETRAN

This study investigates the effect of land use and land cover (LULC) and climate change on catchment hydrology and soil erosion in the Dano catchment in south-western Burkina Faso based on hydrological and soil erosion modeling. The past LULC change is studied using land use maps of the years 1990, 2000, 2007 and 2013. Based on these maps future LULC scenarios were developed for the years 2019, 2025 and 2030. The observed past and modeled future LULC are used to feed SHETRAN, a hydrological and soil erosion model. Observed and modeled climate data cover the period 1990–2030.The isolated influence of LULC change assuming a constant climate is simulated by applying the seven LULC maps under observed climate data of the period 1990–2015. The isolated effect of climate scenarios (RCP4.5 and 8.5 of CCLM4–8) is studied by applying the LULC map of 1990 to the period 1990–2032. Additionally, we combined past modeled climate data and past observed LULC maps. Two chronological and continuous simulations were used to estimate the impact of LULC in the past and in the future by gradually applying the LULC maps. These simulations consider the combined impact of LULC and climate change.The simulations that assumed a constant climate and a changing LULC show increasing water yield (3.6%–46.5%) and mainly increasing specific sediment yield (−3.3%–52.6%). The simulations that assume constant LULC and climate as changing factor indicate increases in water yield of 24.5% to 46.7% and in sediment yield of 31.1% to 54.7% between the periods 1990–2005 and 2006–2032. The continuous simulations signal a clear increase in water yield (20.3%–73.4%) and specific sediment yield (24.7% to 90.1%). Actual evapotranspiration is estimated to change by between −7.3% (only LUCC) to +3.3% (only climate change). When comparing observed LULC and climate change alone, climate change has a larger impact on discharge and sediment yield, but LULC amplifies climate change impacts strongly. However, future LULC (2019–2030) will have a stronger impact as currently observed.

Modeling freshwater quality scenarios with ecosystem-based adaptation in the headwaters of the Cantareira system, Brazil

Abstract. Although hydrologic models provide hypothesis testing of complex dynamics occurring at catchments, freshwater quality modeling is still incipient at many subtropical headwaters. In Brazil, a few modeling studies assess freshwater nutrients, limiting policies on hydrologic ecosystem services. This paper aims to compare freshwater quality scenarios under different land-use and land-cover (LULC) change, one of them related to ecosystem-based adaptation (EbA), in Brazilian headwaters. Using the spatially semi-distributed Soil and Water Assessment Tool (SWAT) model, nitrate, total phosphorous (TP) and sediment were modeled in catchments ranging from 7.2 to 1037 km2. These headwaters were eligible areas of the Brazilian payment for ecosystem services (PES) projects in the Cantareira water supply system, which had supplied water to 9 million people in the São Paulo metropolitan region (SPMR). We considered SWAT modeling of three LULC scenarios: (i) recent past scenario (S1), with historical LULC in 1990; (ii) current land-use scenario (S2), with LULC for the period 2010–2015 with field validation; and (iii) future land-use scenario with PES (S2 + EbA). This latter scenario proposed forest cover restoration through EbA following the river basin plan by 2035. These three LULC scenarios were tested with a selected record of rainfall and evapotranspiration observed in 2006–2014, with the occurrence of extreme droughts. To assess hydrologic services, we proposed the hydrologic service index (HSI), as a new composite metric comparing water pollution levels (WPL) for reference catchments, related to the grey water footprint (greyWF) and water yield. On the one hand, water quality simulations allowed for the regionalization of greyWF at spatial scales under LULC scenarios. According to the critical threshold, HSI identified areas as less or more sustainable catchments. On the other hand, conservation practices simulated through the S2 + EbA scenario envisaged not only additional and viable best management practices (BMP), but also preventive decision-making at the headwaters of water supply systems.

Impact of forecasted land use changes on flood risk in the Polish Carpathians

Flooding is a major environmental hazard in Poland with risks that are likely to increase in the future. Land use and land cover (LULC) have a strong influencing on flood risk. In the Polish Carpathians, the two main projected land use change processes are forest expansion and urbanization. These processes have a contradictory impact on flood risk, which makes the future impact of LULC changes on flooding in the Carpathians hard to estimate. In this paper, we investigate the impact of the projected LULC changes on future flood risk in the Polish Carpathians for the test area of Ropa river basin. We used three models of spatially explicit future LULC scenarios for the year 2060. We conduct hydrological simulations for the current state and for the three projected land use scenarios (trend extrapolation, ‘liberalization’ and ‘self-sufficiency’). In addition, we calculated the amount of flood-related monetary losses, based on the current flood plain area and both actual and projected land use maps under each of the three scenarios. The results show that in the Ropa river, depending on scenario, either peak discharge decreases due to the forest expansion or the peak discharge remains constant—the impact of LULC changes on the hydrology of such mountainous basins is relatively low. However, the peak discharges are very diverse across sub-catchments within the modeling area. Despite the overall decrease of peak discharge, there are areas of flow increase and there is a substantial projected increase in flood-related monetary losses within the already flood-prone areas, related to the projected degree of urbanization.