Modeling Future Hydrological Characteristics Based on Land Use/Land Cover and Climate Changes Using the SWAT Model

Abbaszadeh, Maryam; Bazrafshan, Ommolbanin; Mahdavi, Rasool; Sardooi, Elham Rafiei; Jamshidi, Sajad

doi:10.1007/s11269-023-03545-6

Cited by 15 publications

(7 citation statements)

References 33 publications

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“…Z a and Z b are the standardized values for the variance of the observation values of study units a and c. The distribution map of local indicators of spatial association (LISA) formed can show the clustering and differentiation characteristics of independent and dependent variables in the local region. The SWAT model is widely used in the field of hydrological research [15,20]. In this study, we only used DEM data to generate watershed boundaries and sub-watershed boundaries through SWAT models.…”

Section: Correlation Analysismentioning

confidence: 99%

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Spatial and Temporal Variation in Vegetation Response to Runoff in the Ebinur Lake Basin

Yao,

Wang,

Yang

et al. 2023

Forests

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The response of spatial and temporal vegetation changes to runoff is a complex process involving the interaction of several factors and mechanisms. Timely and accurate vegetation and runoff change information is an important reference for the water cycle and water resource security. The Ebinur Lake Basin is representative of arid areas worldwide. This basin has been affected by climate change and human activities for a long time, resulting in the destruction of the basin’s ecological environment, and especially its vegetation. However, there have been few studies that have focused on watershed vegetation and runoff changes. Therefore, we combined Generalized Information System and remote sensing technology, used SWAT and InVEST models based on the Google Earth Engine platform, and used the vegetation normalization index method to calculate the spatial distribution of vegetation and water production from 2000 to 2020 in Ebinur Lake. Sen’s trend analysis and the M–K test were used to calculate vegetation and runoff trends. The relationship between vegetation and runoff variation was studied using bivariate spatial autocorrelation based on sub-basins and plant types. The results showed that the Z parameter in the InVEST model spanned from 1–2. The spatial distribution of the water yield in a watershed is similar to the elevation of the watershed, showing a trend of higher altitude leading to a higher water yield. Its water yield capacity tends to saturate at elevations greater than 3500 m. The local spatial distribution of the Normalized Difference Vegetation Index(NDVI) values and water yield clustering in the watershed were consistent and reproducible. Interannual runoff based on sub-basins correlated positively with the overall NDVI, whereas interannual runoff based on plant type correlated negatively with the overall NDVI.

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Section: Correlation Analysismentioning

confidence: 99%

“…These projects alter the distribution of natural runoff, thereby affecting hydrological processes [19]. In the Minab River Basin of Iran, the increase in land use has led to a considerable reduction in runoff [20]. When human activities involve water resource development and overuse, water resources are more rapidly depleted [19,21].…”

Section: Introductionmentioning

confidence: 99%

Spatial and Temporal Variation in Vegetation Response to Runoff in the Ebinur Lake Basin

Yao,

Wang,

Yang

et al. 2023

Forests

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“…, and θ 0 is the half angle of the spherical cap, which together with r determines the range of the spherical cap. Then solve Equation (6) for the zeros according to Mueller's method. When the value of n k (m) is determined, the associated Legendre functions can be computed.…”

Section: Spherical Cap Harmonic Analysismentioning

confidence: 99%

“…Surface soil moisture (referred to as SM in the following) is one of the key climatic variables affecting the interaction between atmospheric and terrestrial hydrology [1][2][3]. It profoundly influences agricultural production [4,5], runoff generation [6], drought development [7][8][9], and many other processes. Therefore, timely and accurate information on SM content and its spatial and temporal variability is essential for many applications (e.g., monitoring floods and droughts, irrigation scheduling, improving short-and medium-term meteorological models, and predicting vegetation dynamics) [10].…”

Section: Introductionmentioning

confidence: 99%

Multi-Source Soil Moisture Data Fusion Based on Spherical Cap Harmonic Analysis and Helmert Variance Component Estimation in the Western U.S.

Chen,

Wang

et al. 2023

Sensors

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Soil moisture (SM) is a vital climate variable in the interaction process between the Earth’s atmosphere and land. However, global soil moisture products from various satellite missions and land surface models are affected by inherently discontinuous observations and coarse spatial resolution, which limits their application at fine spatial scales. To address this problem, this paper integrates three diverse types of datasets from in situ, satellites, and models through Spherical cap harmonic analysis (SCHA) and Helmert variance component estimation (HVCE) to produce 1 km of spatio-temporally continuous SM products with high accuracy. First, this paper eliminates the bias between different datasets and in situ sites and resamples the datasets before data fusion. Then, multi-source SM data fusion is performed based on the SCHA and HVCE methods. Finally, this paper evaluates the fused products from three aspects, including the performance of representative sites under different climate types, the overall performance of validation sites, and the comparison with other products. The results show that the fused products have better performance than other SM products. In the representative sites, the minimal correlation coefficient (R) of the fused products is above 0.85, and the largest root mean square error (RMSE) is below 0.040 m3 m−3. For all validation sites, the R and RMSE of the fused products are 0.889 and 0.036 m3 m−3, respectively, while the R for other products is below 0.75 and the RMSE is above 0.06 m3 m−3. In comparison to other SM products, the fused products exhibit superior performance, generally align more closely with in situ measurements, and possess the ability to accurately and finely capture the spatial and temporal variability of surface SM.

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“…Additionally, the process of agricultural water use is accompanied by the emission of greenhouse gases; thus, it also contributes to accelerating global warming [6]. Climate change, since it is driven by greenhouse gas emissions and human activities, exacerbates water resource shortages through altered precipitation patterns and increased evaporation rates [7,8], thereby putting additional stress on regional agricultural economies [9,10]. How to make informed decisions that reduce agricultural water use while maintaining agricultural economic growth and achieving sustainable agriculture goals is an urgent problem that needs to be addressed.…”

Section: Introductionmentioning

confidence: 99%

Dynamics of the Agricultural Water Footprint and the Decoupling Associations with Agricultural Economic Growth in Hangzhou, China

Zhu,

Zhang,

et al. 2023

Water

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Understanding the relationship between the agricultural water footprint (AWF) and agricultural economic growth (AEG) is of great significance for promoting sustainable agriculture and regional economic development. In this study, we used agricultural statistics data from Hangzhou from 2010 to 2021 to calculate the AWF, predicted the decoupling relationship between the AWF and AEG, and explored the influencing factors of the decoupling relationship between the AWF and AEG. The results showed the following: (1) The AWF in Hangzhou exhibited a decreasing trend, with a reduction from 58.88 × 108 m3 in 2010 to 37.80 × 108 m3 in 2021; this was mainly related to the decline in the water footprints of grain, pork, and egg production. (2) The strong decoupling accounted for 63.64% of the decoupling between the AWF and AEG in Hangzhou during the study period. It was found that an agricultural structure adjustment was the main factor for achieving decoupling between the AWF and AEG. Under the guidance of policy, the decoupling between them could be changed by regulating the output of agricultural products with different water footprint contents per unit. (3) From 2022 to 2026, the AWF in Hangzhou is expected to decrease to 28.21 × 108 m3, while the agricultural economy is projected to increase to CNY 40.008 billion. There will continue to be a strong decoupling status between the AWF and AEG in Hangzhou.

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Modeling Future Hydrological Characteristics Based on Land Use/Land Cover and Climate Changes Using the SWAT Model

Cited by 15 publications

References 33 publications

Spatial and Temporal Variation in Vegetation Response to Runoff in the Ebinur Lake Basin

Spatial and Temporal Variation in Vegetation Response to Runoff in the Ebinur Lake Basin

Multi-Source Soil Moisture Data Fusion Based on Spherical Cap Harmonic Analysis and Helmert Variance Component Estimation in the Western U.S.

Dynamics of the Agricultural Water Footprint and the Decoupling Associations with Agricultural Economic Growth in Hangzhou, China

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