Hydrological Components Research Articles

Climate change rather than vegetation greening dominates runoff change in China

China leads the world in vegetation greening and accounts for one-fourth of the global net increase in leaf area over the past two decades. However, it remains elusive on the relative importance of vegetation greening and climate change on China’s hydrological cycle due to the lack of observational-based constraints on notorious model uncertainties. Here, we developed a process-based distributed hydrological model that couples a nonlinear runoff generation mechanism with a remotely-sensed evapotranspiration (ET) module. This model could well capture the spatiotemporal patterns of the main hydrological components (runoff, ET, and soil moisture) at grid scale and streamflow at watershed scale during 1982–2012 over the mainland China. We show that the changes in climatic factors (precipitation and potential ET) dominated hydrologic change at the national scale, with climate induced runoff decrease by 7.6 mm year−1 compared to 0.6 mm year−1 caused by vegetation change. Vegetation effect was primarily notable in water-limited regions as a higher correlation between vegetation contribution to runoff change and absolute leaf area index (LAI) trend in water-limited regions (r = 0.52, p < 0.01) than energy-limited regions (r = 0.19, p < 0.01). Our results highlight the significance of region-dependent differential measures for sustainable water resources management and climate change adaptation under a changing climate.

Hydrological assessment of the Tungabhadra River Basin based on CMIP6 GCMs and multiple hydrological models

AbstractClimate change significantly impacts the natural systems, accelerating the global water cycle, and impacting various ecosystem services. However, the expected effects of climate change on the frequency and severity of extreme events on hydrological systems vary significantly with location. The present study investigates the uncertainties engulfed in hydrological predictions for the Tungabhadra River Basin. The ensemble streamflow projections were generated using four hydrological models, five climate models, and four climate scenarios to illustrate the associated uncertainties. The uncertainty in hydrological components such as streamflow (QQ), water availability (WA), and potential evapotranspiration (PET) was analysed in the future period (2015–2100). The results suggest that, in the monsoon period, precipitation projections increase by about 10.43–222.5%, whereas QQ projections show an increment between 34.50 and 377.7%. The analysis of variance (ANOVA) technique is used to further quantify the contribution of different sources to the total uncertainty. Furthermore, the ensemble spread is optimized using quantile regression forests (QRF), and the post-processed flows are likely to decrease up to 7% in June and increase up to 70% in September. This study is envisaged to give insights into the quantification of uncertainties in the prediction of future streamflow for rational and sustainable policymaking.

Trend analysis of hydro-climate variables in the Jemma sub-basin of Upper Blue Nile (Abbay) Basin, Ethiopia

The change in climate elements such as rainfall and temperature are determinant factors of hydrological components (e.g., streamflow, water yield, evapotranspiration). Thus, understanding the trends of hydro-climate variables are imperative for planning water resources management measures. This study examines the trends of precipitation and temperature (1980–2014) as well as streamflow (1990–2008) changes in the Jemma sub-basin of the Upper Blue Nile (Abbay) Basin. A homogeneity test was performed for pre-processing data to inspect the statistical nature of data homogeneity viz., Pettitt’s, SNHT, Buishand range test, and Von Neumann test (VNT). The Mann–Kendall (MK) test, Modified Mann–Kendall (MMK) test, Sen’s slope estimator, and Innovative trend analysis (ITA) were applied to compute the existence of trend and the magnitude of change at an annual timescale. In a nutshell, the study portrays a change in the trends of hydro-climate variables when using different statistical tests. The result showed that the mean annual temperature in many stations depicted upward trends. There is a significant increasing trend (p < 0.05) by 0.029 °C per year in the mean annual temperature of all climatic stations. Based on Sen’s slope estimator, the annual precipitation and streamflow were increased by 1.781 mm/year and 0.085 m3/s, respectively. But no significant trends were detected in precipitation and streamflow when using Sen’s slope estimator test. The results of this study are worthwhile for evaluating the trends of hydro-climatic variables in other areas of Ethiopia in particular and elsewhere in the world in general, which are fundamental for planning water resource management measures.

Water Recharge Variability Across Serayu Watershed Using Soil Water Assessment Tool (SWAT)

Climate change and land use have an influence on the process of groundwater replenishment. Serayu watershed is categorized as one of the critical watersheds in Indonesia due to groundwater conditions. One that affects groundwater is the ability to replenish groundwater. The purpose of the study was to predict groundwater replenishment in the Serayu watershed. The hydrological model approach (SWAT/Soil Water Assessment Tool) was applied. Spatial data is used in SWAT model analysis, namely: Elevation data, stream, soil types, land use land cover, and climate data. Data analysis using QGIS 3.18 and QSWATPlus tools. The model calibration uses cn2 values while NSE and R2 values are used to evaluate the model. Based on cn2 values, SWAT models show performance that can be used for model implementation. Model validation between before and after the calibration process is (R2) 0.86 while the NSE value is 0.66. When viewed from the water equilibrium ratio, the average water recharge value in the Serayu watershed is 49.5 mm.yr-1 from the total precipitation of 2473.6 mm.yr-1. The largest hydrological component occurs in evapotranspiration and surface runoff (1879.9 and 549.2 mm.yr-1, respectively). The high value of surface runoff indicates that the Serayu watershed needs attention regarding the ability of the land in the water recharge process

Analyzing Groundwater Recharge and Vadose Zone Dynamics by Combining Soil Moisture and Groundwater Level Data with a Numerical Model in Subarctic Conditions

Quantitative estimates on the magnitude and dynamics of vadose and groundwater zones in subarctic conditions are rare. Furthermore, knowledge on the constraints of different data on numerical groundwater recharge estimates (i.e., data worth analyses) is limited. We built a process-based three-dimensional hydrological model to describe and analyze the dynamics and magnitude of groundwater recharge, vadose zone, and related key hydrological components in subarctic conditions. Three-year time series of daily groundwater level and soil moisture (five different depths) data were used to identify plausible model realizations. Thereafter, long-term simulations over 6 years were conducted. The model adequately corresponded with the magnitude and dynamics of the observations, even though the simulations and observations occasionally differed. Simulations with several different plausible parameterizations showed how soil moisture and groundwater level fluctuations, as well as recharge estimates, are sensitive to water retention parameter variations, whereas precipitation and evapotranspiration controlled the recharge magnitude. Recharge showed clear interannual variability (annual mean 0.28–0.60 m). The fraction of annual mean recharge over precipitation was 39%–66% during our simulation period. We showed how groundwater level data can set more constraints on the recharge estimates than soil moisture data, and how both of the data types together constrained the recharge estimates the most. We showed how the vadose zone had modest dynamics and storage properties (typically 2%–8% of the total soil water) in terms of the bulk soil water storage. However, the average amount of the air-filled pore space (0.70 m) and water (0.38 m) in the vadose zone were proportional to annual precipitation and evapotranspiration, respectively. Thus, the vadose zone can form an important boundary between the soil surface and groundwater zone, and its role is not highly sensitive to hydrometeorological fluctuations. Data worth analyses provide a potential opportunity to move toward increasingly reliable model-based groundwater recharge estimates and system understanding.

Drought Assessment of a Data-scarced Watershed – Quetta Valley, Pakistan

Pakistan continuously remains under the threat of drought, as approximately 88% of its area falls under arid and semi-arid regions. The most affected province due to drought is Balochistan, facing migration, scarcity, famine and economic strain. The insufficiency of meteorolgical and hydrological data in the area intensifies the problem because of the late or non-diagnosis of drought. Therefore, this study proposes a methodology to quantify the drought in a watershed with inadequate meteorological and hydrological data. This study aims to design a method to find the extent and duration of drought conditions for watersheds where only basic meteorological data is available. For this purpose, Quetta Valley, Balochistan, Pakistan, is chosen as the study area. First, the hydrological components of water balance for the watershed are calibrated for 10 years using a distributed hydrological model (MIKE-SHE). The modeling results and other observed meteorological data are then used to evaluate eight drought indices to assess the existence and extent of drought, including those which use the hydrological parameters as input from MIKE-SHE. Reconnaissance drought and Palmer drought severity indices, which use detailed hydrological parameters, are found to provide more accurate results coupled with early drought detection of historical events. The results showed that the proposed method could be effectively used to determine the secondary parameters from the hydrological model, which in turn gives more realistic drought conditions for such regions. KEYWORDS: Meteorological drought indices, Hydrological modeling, MIKE SHE, Drought, Palmer drought severity index.

Effects of landscape attributes and climate variables on catchment hydrology

Catchments characteristics, such as geomorphology, geology, soil, land use, and climatic variables, play an important role in total stream flow responses, a critical resource for people and the environment. Most of the previous literatures were applied a conventional statistical regression model to assess the relationship between landscape-climate descriptors, and streamflow and PET. However, a conventional statistical regression model didn’t consider dependence of explanatory variables that were collected or extracted across both space and time. This paper investigated the impacts of landscape attributes and climate variables on catchment scale temporal variation of total streamflow and spatio-temporal variation of potential evapotranspiration (PET) in the Mille catchment using multiple linear regression techniques, and the importance of this study was to test spatial autocorrelation in the spatial regression model which is required to properly assess and quantify the relationship between hydrological regime response components and Landscape-climate descriptors in a catchment with topographically complex, and high spatio-temporal climatic variation like in our case study area, the Mille catchment. Statistical regression analysis revealed significant relationships between streamflow and climate variables, especially with rainfall. Mean maximum temperature is the most dominant factor controlling temporal variation of potential evapotranspiration at a monthly scale, whereas NDVI is the most significant factor that controls the spatial variability of PET. The multiple regression model shows that 91.1% of temporal variation in streamflow was accounted for rainfall, whereas, 96.6% and 78.4% of temporal and spatial variation in potential evapotranspiration was accounted for in maximum temperature and NDVI, respectively. Methods also can be applied to catchments with similar landscape attributes and climate variables.

Integrated assessment of the impact of land use changes on groundwater recharge and groundwater level in the Drava floodplain, Hungary

Land-use/land-cover (LULC) change is considered a key human factor influencing groundwater recharge in floodplains. Without accurate estimations, the impact of LULC change on water balance components may be either significantly understated or exaggerated. This paper assesses the impacts of LULC changes from 1990 to 2018 on water balance components and groundwater levels of the Drava floodplain, Hungary, where human interference has led to a critical environmental situation. In this study, a spatially-distributed water balance model (WetSpass-M), and a groundwater flow model (MODFLOW-NWT) were integrated to assess the impacts of LULC changes. The moderate expansion of built-up areas increased surface runoff, while the afforestation of arable land and meadows and the overgrowth of bare mudflats with willow shrubs increased evapotranspiration. As a consequence, total annual groundwater recharge decreased by 5.3 × 107 m3 in the floodplain with an average of 335 mm year−1 and 317 mm year−1 in 2012 and 2018, respectively. Moreover, an average groundwater level decline by 0.1 m is observed in the same period. Declined groundwater recharge, increased runoff, and evapotranspiration exerted a negative effect on water resources in the Drava basin. The approach tested in this paper allows temporal and spatial estimation of hydrological components under the changes of LULC, providing quantitative information for decision-makers and stakeholders to implement efficient and sustainable management of water resources in the Drava floodplain. The provided integrated model is also applicable to regionally.

Satellite gravity observation and hydrological modelling-based integrated groundwater storage change in Northwestern India

Abstract This paper presents a novel approach for an improved estimate of regional groundwater storage (GWS) change in Northwestern India by integrating satellite-based Gravity Recovery and Climate Exchange (GRACE) gravity observation and hydrological modelling of satellite/in situ hydrometeorological data. Initially, GRACE observation-based terrestrial water storage (TWS) change and hydrological model-based TWS change products were integrated using weight coefficients derived from multi-linear regression analysis of TWS change vs governing hydrological components. Later, the monthly average soil moisture change was subtracted from the monthly average individual and integrated TWS change products to obtain GWS change products. By spatial correlation analysis, three GWS change products were then compared with groundwater level (GWL) fluctuation-based in situ GWS change. Hydrological model, spaceborne GRACE observation, and integrated GWS change products show a positive correlation in ∼59, ∼69, and ∼73% of the area with in situ GWS change. While a hydrological model-based estimate considers geology, terrain, and hydrometeorological conditions, GRACE gravity observation includes groundwater withdrawal from aquifers. All the factors are included in the integrated product. The approach overcomes the limitations of GRACE observation (spatial resolution, geology, terrain, and hydrometeorological factors), hydrological modelling (groundwater withdrawal conditions), and conventional GWL fluctuation-based method (inadequate spatial continuity and cumbersome, labour-intensive exercise).

Using SWAT Model to Estimate the Water Balance of Wadi Al-Mohammadi Basin, Western Iraq

Water balance as a technique is considered one of the means that is relied upon in solving significant hydrological problems. The soil and water assessment tool (SWAT) model was used in this study to assess the water balance in the Wadi Al-Mohammadi basin located at the eastern edge of the Western Desert. Digital elevation model, soil data, Land use - Land cover, and climate data represent the most important requirements for the SWAT model's input as a database. The Wadi Al-Mohammadi basin delineation results show the overall drainage area was 2286.8 km2 with seven sub-basins. The trend line of climate data indicates a clear increase in the total rainfall, relative humidity, temperature, and solar radiation from 1990-2020, while the wind speed decreased during the observed period. The average monthly hydrological components (precipitation, actual evapotranspiration, surface runoff, lateral flow, and deep aquifer recharge) representing the basin's water balance are 68.8 mm, 67 mm, 2.03 mm, 0.02 mm, and 0 mm, respectively.

Penggunaan Korelasi Spearman Untuk Menguji Hubungan Suhu Dan Besarnya Curah Hujan Bulanan di Kota Padang

Rain is one of the important hydrological components. Factors that affect the amount of rainfall in an area are temperature, air humidity, air pressure and wind direction. Previous research stated that there is a strong relationship between temperature and the amount of rainfall. This research was conducted to find out how strong the relationship between the amount of monthly rainfall that occurs in Padang City and the average temperature that occurs in each month for the last 30 years. The research method used is to use quantitative methods using descriptive statistics and non-parametric (spearman correlation test). The selection of the Spearman correlation test was carried out based on the results of the data normality test using the One Sample Anderson-Darling, Ryan-Joiner and Kolmogorov-Smirnov method. Data on temperature and rainfall for the city of Padang are not normal even though they have been normalized using the Box-Cox tranformation method. Spearmen's correlation test shows that there is no significant relationship between the amount of rainfall and temperature with a correlation level of only 9% with a P-Value of 0.087 &gt; 0.05 or 0.001. Further research is needed to find out how strong other factors such as air pressure, humidity and wind direction are on the amount of rainfall in the city of Padang.

Assessing impacts of land use/land cover changes on the hydrology of Upper Gilgel Abbay watershed using the SWAT model

Population and economic growth, and the consequent increase in food demands have put great pressures on environmental resources and they are driving rapid LULC changes. This study is aimed to examine the impacts of land use/land cover LULC changes on the hydrology of the Upper Gilgel Abay watershed. Landsat images (Landsat 5 TM 1986, Landsat ETM+ 2003, and Landsat 8 OLI-TIRS 2021) were categorized into LULC classes following the supervised image classification technique, and the Soil and Water Assessment Tool (SWAT) model was used to evaluate the hydrological impacts of LULC changes. The result of image analysis revealed an increase in cultivated land (11.7%) and a decrease in forest (39.6%), shrubland (17.5%), grassland (5.6%), and water bodies (25%) during 1986–2003 periods. On the other hand, between 2003 and 2021 periods, cultivated land, grassland and water bodies were decreased while woodland and shrubland were grew up. Consequent to the LULC changes taking place between 1986 and 2003 periods, surface runoff (6%) and water yield (1.8%) were increased, but groundwater flow (37.9), lateral flow (4.1), soil water (1.85), and evapotranspiration (2.2%) were decreased at a watershed-scale. In contrast, the average watershed surface runoff and water yield were decreased between 2003 and 2021 time scales, while lateral flow, groundwater flow, soil water, and evapotranspiration increased, owing to the growth of forest and shrubland and the decline of cultivated land. The study also indicated the hydrological impacts of the LULC changes at the sub-watershed scales. The impacts of LULC change on status of hydrological components during 1986–2003 and 2003–2021 periods were different compared with the findings at the watershed scale. The findings suggests improvements of vegetation covers to reduce surface runoff and increase groundwater flow and soil water content in the study area in particular and in the Ethiopian Highlands in general.

Shifted discharge and drier soils: Hydrological projections for a Central Asian catchment

Study RegionThe Naryn River Basin, KyrgyzstanStudy FocusWe investigate the impacts of climate change in the basin based on two families of General Circulation Models (GCMs) using the hydrological model SWAT. The forcing datasets are the widely used ISIMIP2 (I2) and the newly derived ISIMIP3 (I3) data which refer to the 5th and 6th stage of the Coupled Model Intercomparison Project (CMIP). Due to notable differences in the forcing we evaluate their impacts on various hydrological components of the basin, such as discharge, evapotranspiration (ETA) and soil moisture (SM). Besides, a partial correlation (PC) analysis is used to assess the meteorological controls of the basin with special emphasize on the SM-ETA coupling.New Hydrological Insights for the RegionAgreement in the basin’s projections is found, such as discharge shifts towards an earlier peak flow of one month, significant SM reductions and ETA increases. I3 temperature projections exceed their previous estimates and show an increase in precipitation, which differs from I2. However, the mitigating effects do not lead to an improvement in the region’s susceptibility to soil moisture deficits. The PC study reveals enhanced water-limited conditions expressed as positive SM-ETA feedback under I2 and I3, albeit slightly weaker under I3.

Assessment of climate change impact on hydrological components of Ponnaiyar river basin, Tamil Nadu using CMIP6 models

AbstractThis study aims to assess the climate change impacts on the hydrological components in the Ponnaiyar river basin using the Soil Water Assessment Tool (SWAT) model. This study used 13 Global Climate Models (GCM) from Coupled Model Inter-comparison Project Phase 6 (CMIP6). Based on the performance evaluation of 13 CMIP6-GCMs, the best GCMs selected for future projections were EC-Earth3, MPI-ESM1-2-LR and MPI-ESM1-2-HR. SWAT-CUP (SWAT – Calibration and Uncertainty Programs) successfully calibrated and validated the SWAT model. The SWAT model simulated the hydrological components of the basin for the future period under SSP245 and SSP585 emission scenarios. The results indicated increased streamflow over the projected period due to increased rainfall in the basin. The annual surface runoff varied from −20.41 to −15.46%, −10.51 to 18.34% and 73.88 to 134.56% under the SSP585 scenario for the 2020s, 2050s and 2080s, respectively. For the future 2020s, the water yield varied from −7.02 to 11.36% and −1.41 to 6.15% for SSP245 and SSP585. During the 2050s and 2080s, there was an increase in water yield (7.89–21.18% and 36.12–115.25%) under SSP245 and SSP585 future climate scenarios. This study could help policymakers and stakeholders to develop adaptive strategies for the Ponniyar river basin.

Analysis of Long-Term Trend of Stream Flow and Interaction Effect of Land Use and Land Cover on Water Yield by SWAT Model and Statistical Learning in Part of Urmia Lake Basin, Northwest of Iran

The water yield produced at the outlet of a sub-basin is the combination of multiple interacting land uses. In the majority of previous research, while accounting for the effect of land use and land cover (LULC) on water yield, the hydrologic components of a watershed have been attributed to the dominant land use class within that sub-basin. We adopted an approach to investigate the interaction effect of LULC on water yield (WYLD) using the Johnson–Neyman (JN) method. The soil and water assessment tool (SWAT) model was employed in the Urmia Lake Basin (ULB) to estimate the WYLD following successful calibration and validation of the model by stream flow. It was found that in each sub-basin, the effect of the soil class on the WYLD was statistically significant only when the area of rangeland was less than 717 ha and when the area of agricultural lands was less than 633 ha. On the other hand, the trend of stream flow was assessed over 70 years at two stations in the Urmia Lake Basin (ULB) using the Bayesian Estimator of Abrupt change, Seasonal change, and Trend (BEAST). The year 1991 turned out to be the most likely change point in both stations. A significant decrease in Urmia Lake’s water level started in 1995, which indicated that part of this shrinkage was most likely caused by water inflow reduction over a 4-year time delay. Besides identifying the most probable seasonal and trend change points, this method has the additional capability to analyze the uncertainty of estimated points, which was lacking in earlier methods.

Biophysical Benefits Simulation Modeling Framework for Investments in Nature-Based Solutions in São Paulo, Brazil Water Supply System

In order to understand the hydrological impacts of the nature-based solutions in the Cantareira Water Supply System, this study evaluates six different land cover and land use change scenarios. The first and second consider the restoration of native vegetation in riparian areas, the third prioritizes restoration sites using biophysical characteristics (optimized restoration scenario derived from Resource Investment Optimization System—RIOS), the fourth considers best management practices and the fifth and sixth are hypothetical extreme scenarios converting all pasture to forest and vice versa. Two hydrological models were developed to represent the distributions of water and yields in the study watershed: HEC-HMS and SWAT. Simulation results indicate that when nature-based solutions are implemented, surface runoff is reduced and ambient storage increases during the rainy season (December–March); while the overall flow increases during the dry season (June–September). The combination of specific hydrologic components of RIOS-customized intervention scenario simulation outputs—namely surface flows and groundwater contribution to stream flows—indicate on average 33% increase in the overall water yield, or 206 hm3/year, across the study watershed when comparing against the baseline conditions. In the same modeling scenario, the water storage in the sub-watersheds adjacent to the reservoirs showed an increase of 58% (or 341 hm3/year). The results indicate that adopting NbS in the source watershed can mitigate the impacts of extreme drought conditions and contribute toward building long-term water security.

Assessment of Water Balance of Deme Watershed, Omo-Gibe Basin, Ethiopia Using SWAT Model and ARC-GIS for Water Resources Management

To deal with water management issues, one must analyse and quantify the different elements of hydrologic processes taking place within the area of interest. Obviously, this analysis must be carried out on a watershed basis because all these process are taking place within individual micro watersheds. Only after understanding the spatial and temporal variation and the interaction of these hydrologic components one can scientifically formulate strategies for water conservation. To achieve this goal the choice and use of an appropriate watershed model is a must. All the thematic maps and attribute information of the watershed have been collected from various Government agencies. SWAT model has been set up for the Deme watershed by inputting the digital thematic maps, physical properties of soil and climatic parameters. Total area of the watershed corresponding to the outlet chosen at Deme watershed is 11284.35km ² and its elevation varies from 1138 to 3269m. Calibration and validation of the model have been done by comparing the river flow prediction with the observed values. Nash Sutcliff Efficiency (NSE), coefficient of determination (R ²) and Percent bias (PBIAS) has given very high values for the calibration 0.75, 0.75 and -0.7% respectively and validation 0.73, 0.74 and 6.3% respectively. The calibrated model has been used to predict the important hydrologic processes. The water balance components of Deme watershed resulted PET 388.5mm, Evaporation and transpiration 293.8mm, Precipitation 1147.5mm, Average curve number 76.38, Surface runoff 189.7mm, Revap from shallow aquifer 7.7mm, Percolation to shallow aquifer 37.59mm, Lateral flow 624.33mm and Recharge to deep aquifer 0.28mm. The study has revealed that SWAT model can effectively be used in the simulation of river flow and for predicting the water balance of a watershed. Water balance information of the basin is of great use in planning water conservation, drainage and flood control.

Influence of hydrological state on trophic state in dam induced seasonally inundated flood plain wetland

A Good many research works focused on investigating wetland habitat state and trophic state (TS) but as far the knowledge is concerned, very little attention was paid to the hydrological state (HS) modelling of wetlands, and no such attention was paid on exploring the linkage between HS and TS. But it is very essential to explore the role of hydrological characters on TS in order to frame hydrological management strategies. Considering this, the present study intended to build HS models using image-driven hydrological components like water presence frequency, hydro-period, water depth; to estimate trophic state index (TSI) using field-driven water samples and, finally linking HS and TSI of the wetland. Successful results can open up a new approach to improve the strategies for water quality and ecological efficiency management. Machine learning models were applied for building the HS model and Carlson's TSI method was applied to explore water quality and ecological state. The ordinary least square regression was applied for linking HS and TSI. Results showed that hydrological modification and associated causes obliterated 32.32 km2 of wetland between the pre-dam and post-dam periods. The support vector machine model was found as the best-suited HS model to all the applied models. TSI was found poor over a wider part of the wetland, especially over the hydrologically poor patches of the wetland. The hydrological worsening is a cause for the worsening of TS. So, it can be stated that managing hydrological components is a good way to manage TS.

Impacts of climate change and fruit tree expansion on key hydrological components at different spatial scales

Assessing how fruit tree expansion and climate variability affect hydrological components (e.g., water yield, surface runoff, underground runoff, soil water, evapotranspiration, and infiltration) at different spatial scales is crucial for the management and protection of watersheds, ecosystems, and engineering design. The Jiujushui watershed (259.32 km2), which experienced drastic forest changes over the past decades, was selected to explore the response mechanisms of hydrological components to fruit tree expansion and climate variability at different spatial scales (whole basin and subbasin scale). Specifically, we set up two change scenarios (average temperature increase of 0.5°C and fruit tree area expansion of 18.97%) in the SWAT model by analyzing historical data (1961∼2011). Results showed that climate change reduced water yield, surface runoff, and underground runoff by 6.75, 0.37, and 5.91 mm, respectively. By contrast, the expansion of fruit trees increased surface runoff and water yield by 2.81 and 4.10 mm, respectively, but decreased underground runoff by 1 mm. Interestingly, the sub-basins showed different intensities and directions of response under climate change and fruit tree expansion scenarios. However, the downstream response was overall more robust than the upstream response. These results suggest that there may be significant differences in the hydrological effects of climate change and fruit tree expansion at different spatial scales, thus any land disturbance measures should be carefully considered.

Modeling Daily Reference Evapotranspiration from Climate Variables: Assessment of Bagging and Boosting Regression Approaches

The increasing frequency of droughts and floods due to climate change has severely affected water resources across the globe in recent years. An optimal design for the scheduling and management of irrigation is thus urgently needed to adapt agricultural activities to the changing climate. The accurate estimation of reference crop evapotranspiration (ET0), a vital hydrological component of the water balance and crop water need, is a tiresome task if all the relevant climatic variables are unavailable. This study investigates the potential of four ensemble techniques for estimating precise values of the daily ET0 at representative stations in 10 agro-climatic zones in the state of Karnataka, India, from 1979 to 2014. The performance of these models was evaluated by using several combinations of climatic variables as inputs by using tenfold cross-validation. The outcomes indicated that predictions of ET0 by all four ensemble models based on all climatic variables were the most accurate in comparison with other input combinations. The random forest regressor was found to deliver the best performance among the four models on all measures considered (Nash–Sutcliffe efficiency, 1.0, root-mean-squared error, 0.016 mm/day, and mean absolute error, 0.011 mm/day). However, it incurred the highest computational cost, whereas the computational cost of the bagging model for linear regression was the lowest. The extreme gradient-boosting model delivered the most stable performance with a modified training dataset. The work here shows that these models can be recommended for daily ET0 estimation based on the users’ interests.