Land-Use/Land Cover Changes Contribute to Land Surface Temperature: A Case Study of the Upper Indus Basin of Pakistan

Land-use/land cover (LULC) changes have an impact on land surface temperature (LST) at the local, regional, and global scales. To simulate the LULC and LST changes of the environmentally important area of northern Pakistan, this research focused on spatio-temporal LULC and associated LST changes since 1987 and made predictions to 2047. We classified LULC from Landsat TM and ETM data, using the maximum probability supervised categorization approach. LST was retrieved using the Radiative Transfer Equation (RTE) methodology. Furthermore, we simulated LULC using the integrated approaches of Cellular Automata (CA) and Weighted Evidence (WE) and used a regression model to predict LST. The built-up areas and vegetation have increased by 2.1% and 11% due to a decline in the barren land by −8.5% during the last 30 years. The LULC is expected to increase, particularly the built-up and vegetation classes by 2.74% and 13.66%, respectively, and the barren land would decline by −4.2% by 2047. Consequently, the higher LST classes (i.e., 27 °C to <30 °C and ≥30 °C) soared up by about 25.18% and 34.26%, respectively, during the study period, which would further expand to 30.19% and 14.97% by 2047. The lower LST class (i.e., 12 °C to <21 °C) indicated a downtrend of about −41.29% and would further decrease to −3.13% in the next 30 years. The study findings are useful for planning and management, especially for climatologists, land-use planners, and researchers in sustainable land use with rapid urbanization.

Impacts of Climatic Variation and Human Activity on Runoff in Western China

Hydrological cycle is sensitively affected by climatic variation and human activity. Taking the upper- and middle-stream of the Weihe River in western China as an example, using multiple meteorological and hydrological elements, as well as land-use/land-cover change (LUCC) data, we constructed a sensitivity model of runoff to climatic elements and human activities based on the hydro-thermal coupling equilibrium equation, while a cumulative slope was used to establish a comprehensive estimation model for the contributions of climatic variation and human activities to the changes of runoff. The results showed that the above function model established could be well applied to quantitatively study the elasticity of runoff’s response to climatic variation and human activities. It was found that the annual average precipitation, evaporation, wind velocity, sunshine hours, relative humidity and runoff showed decreasing trends and that temperature increased. While in the hydrological cycle, precipitation and relative humidity had a non-linear positive driving effect on runoff, while temperature, evaporation, sunshine hours, wind velocity, and land-use/land-cover change (LUCC) have non-linearly negatively driven the variation of runoff. Moreover, runoff has a strong sensitive response to precipitation, evaporation and LUCC. In areas with strong human activities, the sensitivity of runoff to climatic change was decreasing, and runoff has a greater elastic response to underlying surface parameters. In addition, the analysis showed that the abrupt years of climate and runoff changes in the Weihe River Basin were 1970, 1985 and 1993. Before 1985, the contribution rate of climatic variation to runoff was 68.3%, being greater than that of human activities to runoff, and then the contribution rates of human activities to runoff reached 75.1%. The impact of natural climate on runoff was weakened, and the effect of human activities on runoff reduction increased. Under 30 hypothetical climatic scenarios, the evaluation of runoff in the future showed that the runoff in the Weihe River Basin will be greatly reduced, and the reduction will be more significant during the flood season. Comparing the geographically fragile environments and intense human activities, it was believed that climatic variation had a dramatic effect on driving the water cycle of precipitation and evaporation and affected regional water balance and water distribution, while human activities had driven the hydrological processes of the underlying surface, thus becoming the main factors in the reduction of runoff. This study provided scientific tools for regional climate change and water resources assessment.

Effects of Land Use Land Cover and Slope Gradients on Soil Fertility at Kori Sub-Watershed, East Wollega, Ethiopia

BackgroundThe complex nature of the relationship and interaction between LULC and slope gradients resulted in the decline of soil fertility parameters, which aggravate the reduction of sustainable productivity in Ethiopia in general and the study area in particular. This study was aimed to determine the effects of land use land cover and slope gradients on the physicochemical properties of soil in study area A total of 27 composite soil samples were collected from 0-20cm depth under three dominant adjacent LULC across three slope with three replications. The collected soil samples were analyzed for selected soil physicochemical properties. Two-way ANOVA was used to test the mean differences of the soil fertility parameters. ResultThe mean values of soil physicochemical parameters showed that, SOC, TN, AvP, CEC, exchangeable bases (Ca2+ Mg2+, K+, and Na+), PBS, and percentage of clay contents of cultivated land and steep slope gradient (15-30%) were low and significantly different at (P≤0.05) than forest and grad grassland of the same slope gradient.. The gentle slope (3-8%) gradients of the forest lands had the lowest BD and high TP as compared to the others.ConclusionThe overall soil fertility status of the steep slope gradient (15-30%) of cultivated lands is lower than others and cultivating the steep slope is the cause for productivity loss in the study sub-watershed. Therefore, proper land-use planning and the use of integrated soil fertility management strategy give better production and keep the soil fertility status to a better level.

Impact of urban expansion on continental- to regional-scale warming

Although the influence of land use/land cover change on climate has become increasingly apparent, cities and other built-up areas are usually ignored when estimating large-scale historical climate change or for future projections since cities cover a small fraction of the terrestrial land surface1,2. As such, ground-based observations of urban near-surface meteorology are rare and most earth system models do not represent historical or future urban land cover3–7. Here, by combining global satellite observations of land surface temperature with historical estimates of built-up area, we demonstrate that the urban temperature signal on continental- to regional-scale warming has become non-negligible, especially for rapidly urbanizing regions in Asia. Consequently, expected urban expansion over the next century suggest further increased urban influence on surface climate under all future climate scenarios. Based on these results, we argue that, in line with other forms of land use/land cover change, urbanization should be explicitly included in future climate change assessments. This would require extensive model development to incorporate urban extent and biophysics in current-generation earth system models to quantify potential urban feedbacks on the climate system at multiple scales.

Modeling the Impact of Climate and Land Use/Land Cover Change on Water Availability in an Inland Valley Catchment in Burkina Faso

Water scarcity for smallholder farming in West Africa has led to the shift of cultivation from uplands to inland valleys. This study investigates the impacts of climate and land use/land cover (LULC) change on water resources in an intensively instrumented inland valley catchment in Southwestern Burkina Faso. An ensemble of five regional climate models (RCMs) and two climate scenarios (RCP 4.5 and RCP 8.5) was utilized to drive a physically-based hydrological model WaSiM after calibration and validation. The impact of climate change was quantified by comparing the projected period (2021–2050) and a reference period (1971–2000). The result showed a large uncertainty in the future change of runoff between the RCMs. Three models projected an increase in the total runoff from +12% to +95%, whereas two models predicted a decrease from −44% to −24%. Surface runoff was projected to show the highest relative change compared to the other runoff components. The projected LULC 2019, 2025, and 2030 were estimated based on historical LULC change (1990–2013) using the Land Change Modeler (LCM). A gradual conversion of savanna to cropland was shown, with annual rates rom 1 to 3.3%. WaSiM was used to simulate a gradual increase in runoff with time caused by this land use change. The combined climate and land use change was estimated using LULC-2013 in the reference period and LULC-2030 as future land use. The results suggest that land use change exacerbates the increase in total runoff. The increase in runoff was found to be +158% compared to the reference period but only +52% without land use change impacts. This stresses the fact that land use change impact is not negligible in this area, and climate change impact assessments without land use change analysis might be misleading. The results of this study can be used as input to water management models in order to derive strategies to cope with present and future water scarcities for smallholder farming in the investigated area.

Scale Effects on the Calculation of Ecosystem Service Values: A Comparison among Results from Different LULC Datasets

Land use/land cover (LULC) has an important impact on the ecological environment and is crucial for calculating ecosystem service values (ESVs). However, whether and to what extent the ESVs vary when calculated by LULC product data at different spatial scales remain unclear. Data from two LULC products were used in this study, and two datasets with different spatial scales were obtained by resampling. Then, the ESVs were calculated by the equivalent factor method. Finally, the impacts of LULC on ESVs at different scales were studied, revealing the following: (1) The ESVs calculated by LULC products and by the same products at different scales are different. (2) The difference in the ESVs calculated by the two LULC datasets is approximately 28%, and the difference tends to decrease with increasing scale. (3) With an increase in the LULC scale, the overall change trend of ESVs also increases, and the increasing trend gradually moderates. In addition, the ESVs and LULC scale conform to a logarithmic relationship, and the coefficient of determination (R2) is greater than 0.7. These results have important reference value for obtaining reliable ESVs.