Influence of changes in land use and land cover and rainfall on the streamflow regime of a watershed located in the transitioning region of the Brazilian Biomes Atlantic Forest and Cerrado

Filho

Rev. bras. eng. agríc. ambient.

et al. 2023

The Cerrado biome has presented challenges in reconciling its agricultural expansion with water availability. In this sense, water resources planning and management are fundamental for the economic, social, and environmental development of the Cerrado biome, which has been hampered by the lack of data, especially those referring to irrigation strategies, such as, for example, the water retention curve. The water retention curve is essential to understand water dynamics in the soil; however, obtaining it can be laborious, opening an opportunity for Pedotransfer Functions (PTFs). The current study aimed to develop and evaluate PTFs to estimate the fit parameters of the van Genuchten model for the Cerrado biome. Multiple Linear Regression (MLR) and four machine learning (ML) algorithms were used to develop the PTFs. The ML algorithms were the Multivariate Adaptive Regression Splines (MARS), Random Forest (RF), Support Vector Regression (SVR), and K Nearest Neighbors (KNN). Two combinations of soil data were evaluated, and the predictor variables used in each set were different. Using the RF and SVR models, the best estimates were obtained concerning the parameter θs (saturated water content). As for θr (residual water content), the models showed a moderate predictive capacity. For the other parameters, the models did not perform satisfactorily for α and n (fit parameters).

Section: Introductionmentioning

confidence: 99%

Pedotransfer functions for estimating the van Genuchten model parameters in the Cerrado biome

Filho

Rev. bras. eng. agríc. ambient.

et al. 2023

“…Although the importance of studying the relationships between the runoff-erosion process and LULCC using remote sensing multiple gridded datasets is well-understood, determining the spatial distribution of the runoff-erosion process is an essential prerequisite for the establishment of erosion management plans in any catchment. The advancement of agriculture and the influence of different LULC scenarios has been significantly studied [7][8][9][10]; however, research involving the impacts of LULC on runoff-erosion processes using estimated satellite data and runoff-erosion models in some regions of the planet, such as Brazil, is still scarce [11][12][13]. In addition, the published studies did not carry out estimates of runoff and sediment yield considering different LULC scenarios at watershed scales.…”

Section: Introductionmentioning

confidence: 99%

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

Fonseca

Al‐Ansari

Silva

et al. 2022

IJGI

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.

Journal of Water and Climate Change

“…However, a quantification of its magnitude at the regional level under future climate change scenarios is a challenging task (Bisht et al 2018). Several climatic indices based on long-term datasets of precipitation and temperature have been developed and used by researchers to identify and quantitatively examine the variations in weather patterns and extreme weather events due to climate change (Duan et al 2016;de Oliveira Souza et al 2018;Talchabhadel & Karki 2019;Ferreira et al 2021;Teixeira et al 2021).…”

Section: Introductionmentioning

confidence: 99%

“…Any shift in the behaviour of this critical hydro-climatic variable is not evenly distributed over all regions; rather, it has its own distinct local component (Bisht et al 2018). Scientists across different parts of the world have conducted research on climate change and have attempted to decipher the trajectory of various climate indices (Duan et al 2016;de Oliveira Souza et al 2018;Talchabhadel & Karki 2019;Ferreira et al 2021;Teixeira et al 2021). An analysis of the prevailing trends in climate conditions using long-term meteorological data is very important for climate change studies.…”

Section: Introductionmentioning

confidence: 99%

Spatio-temporal trend analysis and future projections of precipitation at regional scale: a case study of Haryana, India

Chauhan

Singh

Maurya

et al. 2022

In this study, we investigated the spatio-temporal distribution and performance of seasonal precipitation in all districts of Haryana, India. We analysed the gridded precipitation dataset of the India Meteorological Department (IMD) for a period of 120 years (1901–2020) using different statistical methods. We found that Haryana received a mean precipitation of 37.0, 37.7, 468.3, and 24.8 mm during the winter, pre-monsoon, monsoon, and post-monsoon seasons, respectively. During each season, the eastern districts of Haryana received more precipitation than its western counterparts. Sen's slope results obtained after trend-free pre-whitening (TFPW) showed a statistically significant increasing trend of 0.12 mm (p-value; 0.04) during the pre-monsoon period, whereas decreasing but non-significant trends were observed during the winter, monsoon and post-monsoon seasons at the rate of −0.04 mm (p-value; 0.49), −0.26 mm (p-value; 0.52), −0.05 mm (p-value; 0.33) per year, respectively, for the entire Haryana state. The winter precipitation is expected to increase under the Representative Concentration Pathway 4.5 (RCP4.5) scenario, whereas pre-monsoon precipitation is expected to decrease under the RCP8.5 scenario by the end of the 21st century. The monsoon precipitation is expected to decrease under all RCP scenarios, whereas post-monsoon precipitation is expected to gradually increase under the RCP8.5 scenario by the end of the 21st century.