Modelling the impact of climate and land cover change on hydrology and water quality in a forest watershed in the Basque Country (Northern Spain)

Peraza-Castro, M.; Ruiz‐Romera, Estilita; Meaurio, Maite; Sauvage, Sabine; Sánchez‐Pérez, José‐Miguel

doi:10.1016/j.ecoleng.2018.07.016

Cited by 25 publications

(7 citation statements)

References 52 publications

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“…We calculated the percentage of rivers of Table 3 the statistics criteria R 2 , NSE, PBIAS and KGE. According to Moriasi [13,74], we considered the performances of the model succeed when R 2 , is This study explores an alternative methodology to model water quantity and quality resources at multiple scales, for the first time, by coupling various data sources (agricultural, urban effluents, quality and quantity data) at the SUDOE scale-that has been never approached [101][102][103]. Previous studies made analysis on uncalibrated simulations [9] or calibrated only on streamflow [11].…”

Section: Limitations and Uncertainties Of This Studymentioning

confidence: 99%

Hydrological Alteration Index as an Indicator of the Calibration Complexity of Water Quantity and Quality Modeling in the Context of Global Change

Cakir

Raimonet

Sauvage

et al. 2019

Water

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Modeling is a useful way to understand human and climate change impacts on the water resources of agricultural watersheds. Calibration and validation methodologies are crucial in forecasting assessments. This study explores the best calibration methodology depending on the level of hydrological alteration due to human-derived stressors. The Soil and Water Assessment Tool (SWAT) model is used to evaluate hydrology in South-West Europe in a context of intensive agriculture and water scarcity. The Index of Hydrological Alteration (IHA) is calculated using discharge observation data. A comparison of two SWAT calibration methodologies are done; a conventional calibration (CC) based on recorded in-stream water quality and quantity and an additional calibration (AC) adding crop managements practices. Even if the water quality and quantity trends are similar between CC and AC, water balance, irrigation and crop yields are different. In the context of rainfall decrease, water yield decreases in both CC and AC, while crop productions present opposite trends (+33% in CC and −31% in AC). Hydrological performance between CC and AC is correlated to IHA: When the level of IHA is under 80%, AC methodology is necessary. The combination of both calibrations appears essential to better constrain the model and to forecast the impact of climate change or anthropogenic influences on water resources.

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Section: Limitations and Uncertainties Of This Studymentioning

confidence: 99%

Hydrological Alteration Index as an Indicator of the Calibration Complexity of Water Quantity and Quality Modeling in the Context of Global Change

Cakir

Raimonet

Sauvage

et al. 2019

Water

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“…These studies have shown that CA models are efficient in producing practical simulations of land cover patterns and other spatial structures. CA algorithm is an extension of the land change modeller (LCM) to help predict LC changes using the descriptive variables such as elevation, slope, aspect, and distance from specific areas (Gu et al, 2019; Peraza‐Castro et al, 2018; Sangermano et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

Analysis and prediction of land cover changes using the land change modeler (LCM) in a semiarid river basin, Iran

et al. 2021

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Predicting future land cover (LC) changes is an important step in the proper planning and management of watersheds. As a susceptible area to salinity and desertification, receiving only about 195 mm rainfall annually, the Hable‐Rud River basin is especially sensitive to land use/cover changes. Based on corrected LANDSAT satellite images for the years 1986, 2000, and 2017, the LC were extracted using the maximum likelihood (ML) method. LC changes were predicted by applying the land change modeler (LCM) for the basin. The kappa index for classification in 1986, 2000, and 2017 was 75, 78, and 81%, respectively. Using LCM, the prediction was accomplished for the year 2017 with a kappa index of above 74%. The LC map was predicted for year 2040. The analysis indicates that over the past 32 years, bare land, saline land, agricultural, industrial, and residential areas have increased by about 8, 6.2, 2.7, 0.63, and 0.48%, respectively; while rangeland area was decreased by 18%. Results also indicate that given the predicted LC for year 2040 in comparison with the reference year (2017), saline land, agricultural, industrial, and residential areas will be likely to continue to increase by about 3, 1.5, 0.7, and 0.8%, respectively, whereas bare land and rangeland will most likely decrease by about 4.55 and 1.45%, respectively. The findings of this study assist in analyzing the future trends of LC changes in the basin. This information can be used as a guide for land planners and managers in future land use planning of the area.

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“…Compared with the previous non-point source pollution models, the hydrologic research unit (HRU) was taken as the compute unit in the SWAT model for calculations [16], and the simulation efficiency was significantly improved. The SWAT has achieved fruitful research results in different fields, such as the impact of climate change and human activities [17][18][19], the impact of land use change [20][21][22], hydrological circulation simulation [23][24][25], sediment loss calculation [26][27][28], discussion on the law of nutrient loss [2,29,30], assessment of the impact on the ecological environment [31][32][33], and the evaluation of optimized management measures for non-point source pollution [34,35]. In China, the SWAT models have also been applied in important regions such as the Yangtze River watershed [36], the Three Gorges Reservoir Area [37,38], and Taihu Lake [39].…”

Section: Introductionmentioning

confidence: 99%

Sub-Watershed Parameter Transplantation Method for Non-Point Source Pollution Estimation in Complex Underlying Surface Environment

Chen

Liu

et al. 2021

Land

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The prevention and control of non-point source pollution is an important link in managing basin water quality and is an important factor governing the environmental protection of watershed water in China over the next few decades. The control of non-point source pollution relies on the recognition of the amount, location, and influencing factors. The watershed nonpoint source pollution mechanism model is an effective method to address the issue. However, due to the complexity and randomness of non-point source pollution, both the development and application of the watershed water environment model have always focused on the accuracy and rationality of model parameters. In this pursuit, the present study envisaged the temporal and spatial heterogeneity of non-point source pollution caused by the complex underlying surface conditions of the watershed, and the insufficient coverage of hydrological and water quality monitoring stations. A refined watershed non-point source pollution simulation method, combining the Monte Carlo analytic hierarchy process (MCAHP) and the sub-watershed parameter transplantation method (SWPT), was established on the basis of the migration and transformation theory of the non-point source pollution, considering the index selection, watershed division, sub-watershed simulation, and parameter migration. Taking the Erhai Lake, a typical plateau lake in China, as the representative research object, the MCAHP method effectively reduced the uncertainty of the weights of the watershed division indexes compared to the traditional AHP method. Furthermore, compared to the traditional all watershed parameter simulation (AWPS) approach, the simulation accuracy was improved by 40% using the SWPT method, which is important for the prevention and control of non-point source pollution in large-scale watersheds with significant differences in climatic and topographic conditions. Based on the simulation results, the key factors affecting the load of the non-point source pollution in the Erhai watershed were identified. The results showed that the agricultural land in Erhai Lake contributed a majority of the load for several reasons, including the application of nitro phosphor complex fertilizer. Among the different soil types, paddy soil was responsible for the largest pollution load of total nitrogen and total phosphorus discharge into the lake. The zones with slopes of 0°‒18° were found to be the appropriate area for farming. Our study presents technical methods for the assessment, prevention, and control of non-point source pollution load in complex watersheds.

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Modelling the impact of climate and land cover change on hydrology and water quality in a forest watershed in the Basque Country (Northern Spain)

Cited by 25 publications

References 52 publications

Hydrological Alteration Index as an Indicator of the Calibration Complexity of Water Quantity and Quality Modeling in the Context of Global Change

Hydrological Alteration Index as an Indicator of the Calibration Complexity of Water Quantity and Quality Modeling in the Context of Global Change

Analysis and prediction of land cover changes using the land change modeler (LCM) in a semiarid river basin, Iran

Sub-Watershed Parameter Transplantation Method for Non-Point Source Pollution Estimation in Complex Underlying Surface Environment

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