Evapotranspiration Losses Research Articles

Reforestation effects on low flows: Review of public perceptions and scientific evidence

AbstractThis review article focuses on the complex relationships between forests and water, particularly the effects of forests on streamflow during meteorological droughts. The impact of forests on water resources is a long‐standing research topic, but there are also many common beliefs that are not based on scientific evidence or only selective evidence. We critically examine the origin of some of the common public misconceptions and review the wealth of studies on how forests impact precipitation, soil water dynamics, evapotranspiration, and streamflow. Generally, reforestation increases evapotranspiration and decreases groundwater recharge and streamflow. However, some of the evaporated water will return as precipitation, potentially offsetting some of the increased evapotranspiration losses. Where reforestation leads to more extensive infiltration and recharge due to the effects of forests on the soil's hydraulic properties, it might increase streamflow during dry periods. Although these individual processes have been studied, predicting the impacts of forests on streamflow remains challenging as the effects are site‐specific and depend on many factors, such as the climate, the forest‐ and soil‐characteristics before and after reforestation, and the hydrogeological setting. However, a more accurate and nuanced understanding of the role of forests on hydrology and a better ability to predict where and when the net effects of reforestation are positive or negative is crucial for sustainable forest and water management.This article is categorized under: Science of Water > Science of Water Science of Water > Water and Environmental Change Science of Water > Hydrological Processes Engineering Water > Sustainable Engineering of Water

Enhanced relationship between seasonal soil moisture droughts and vegetation under climate change over China

Climate change could intensify seasonal soil moisture droughts and subsequently degrade vegetation, but it can also facilitate vegetation growth with the rising temperature and CO2 concentrations. Therefore, the change of the vegetation-drought relationship under climate change remains elusive. Here, we investigate the effects of vegetation greening (i.e., increasing leaf area index (LAI)) on seasonal soil moisture drought trends by performing a set of land surface model simulations with the Conjunctive Surface-Subsurface Process model version 2 (CSSPv2), as well as the impact of seasonal soil moisture drought change on vegetation productivity via a statistical fitting model. Our results indicate that both the impact of increasing LAI on exacerbating seasonal droughts and the impact of increasing seasonal droughts on reducing vegetation productivity have been enhanced over China during 1961–2018. Specifically, increased LAI accounts for 48 % of the rising drought frequency through escalated evapotranspiration losses, with more pronounced effects in northern semiarid regions. The decrease in vegetation stomatal conductance caused by rising CO2 concentrations limits transpiration and alleviates 11 % of the increase in drought frequency, but it cannot fully offset the drought aggravation induced by increased vegetation water consumption under climate warming. Meanwhile, increased drought frequency and intensity have reduced the upward trend in vegetation productivity by 5 % over China, and by 8 % in water-limited northern regions. Our study shows the relationship between seasonal soil moisture droughts and vegetation over China has strengthened, indicating that vegetation greening will lead to increased water shortages and further impact vegetation growth and carbon sequestration. This challenges water resources management and environmental sustainability, especially in semiarid regions.

The energy-limited water loss of an alpine shrubland on the northeastern Qinghai-Tibetan Plateau, China

Study regionAlpine shrubland on the northeastern Qinghai-Tibetan Plateau. Study focusWater provision ability is a pivotal ecological service of high-altitude alpine regions and is controlled by precipitation, evapotranspiration (ET), and soil water storage whereas the underlying ecohydrological processes remain highly unquantified. Here, we investigated continuous 19-year flux measurements to quantify the temporal patterns of ET and water budget (precipitation minus ET, P−ET), as well as 0-20 cm soil water storage change (ΔSWS). New hydrological insights for the regionAt a monthly scale, ET peaked in July (96.7 ± 26.4 mm, Mean ± S.D.) and averaged 41.7 ± 31.9 mm, whose variations were determined by the slope of the saturation vapor pressure curve at air temperature, air and soil temperatures, regardless of vegetation growth stage. P−ET averaged 18.3 ± 26.3 mm in August and September while stayed deficit during the other months. The variations in P−ET were controlled by precipitation in the May-October growing season whereas by ET in the non-growing season from November to April. ΔSWS peaked in May (28.8 ± 11.2 mm) and September (3.0 ± 2.7 mm) and almost accumulated to zero over the whole season. At annual scales, none of ET, P−ET, and ΔSWS changed significantly. ET averaged 512.2 ± 68.4 mm and exceeded precipitation (459.1 ± 58.4 mm), likely due to the lateral flow supply of uphill locations. The variations in ET were regulated directly by bulk canopy resistance and indirectly by net radiation. P−ET averaged −53.2 ± 95.4 mm and demonstrated a clear water deficit (−51.6 ± 21.0 mm) during the non-growing season. The variations of P−ET were driven jointly by precipitation and ET, with opposite but equivalent effects. The dominance of thermal conditions and energy availability on ET variability manifested an energy-limited feature of water loss in the alpine shrubland. The temporal patterns in P−ET elucidated that the alpine shrubland plays the water retention rather than water provision function through transforming variable precipitation input into stable ET loss.

Water Budget for Lake Trafford, a Natural Subtropical Lake in South Florida: An Example of Enhanced Groundwater Influx in a Subtropical Lake Subsequent to Organic Sediment Dredging

A very detailed water budget analysis was conducted on Lake Trafford in South Florida. The inflow was dominated by surface water influx via five canals (61%), with groundwater influx constituting 12% and direct rainfall constituting 27%. Lake discharge was dominated by sheet flow (69%) and evapotranspiration (30.5%), with groundwater recharge of the hydraulically connected unconfined aquifer accounting for only 0.5%. The removal of 30 M tons (4.4 × 106 m3) of organic sediment impacted the groundwater influx, causing enhanced groundwater flow into the deeper parts of the lake and mixed flow along the banks, creating a rather unusual pattern. The large number of groundwater seepage meters used during this investigation led to a very reliable set of measurements with occasional failure of only a few meters. A distinctive relationship was found between the wet-season lake stage, heavy rainfall events, and pulses of exiting sheet flow from the lake. Estimation of the evapotranspiration loss using data collected from a weather station on the lake allowed the use of three different models, which, when averaged, produced results comparable to Lake Okeechobee (South Florida). A limitation of this investigation was the inability to directly measure sheet-flow discharges, which had to be estimated as a residual within the calculated water budget.

Woody Biochar Rate and Water Shortage Impact on Early Growth Stages of Chenopodium quinoa Willd.

The application of biochar to agricultural soils has been proven to have many advantages, including the improvement of soil water holding capacity and plant growth, particularly under limiting conditions of water supply. The response of quinoa (Chenopodium quinoa Willd.) to water shortage occurring during the vegetative growth stages is not well known. Therefore, the present study aimed to evaluate the combined effects of three wood chip biochar rates (0%, 2% and 4%) and two water regimes (100 and 50% evapotranspiration losses restitution) on the vegetative development and water status of quinoa (cultivar Titicaca). The results showed that the treatment with 2% wood chip biochar improved plant height, leaf and branch number and stem diameter during the vegetative growing cycle compared to the 0% (control) and 4% biochar treatments, which were not different from each other. At the end of the experiment, when the plants were at the flowering initiation stage, increases of 23% in leaf area, 22% in fresh biomass, 27% in main panicle length and 36% in sub-panicle number were observed. The application of woody biochar at a 4% rate, although improving the plant water status with increases of 10% in RWC and 18% in Ψ, did not enhance the vegetative development of the quinoa. The water shortage negatively affected both the growth performance and plant water status. The best growth response of quinoa was observed only when the plants were treated with a 2% biochar rate and were fully irrigated.

Inducing Evapotranspiration Reduction in an Engineered Natural System to Manage Saltcedar in Riparian Areas of Arid Environments

Many management practices have been implemented to control non-native saltcedar (Tamarix spp.) in the Southwestern U.S. riparian areas. These management practices include herbicide application, mechanical and biological control. Despite these methods have had some success, they are not cost-efficient and some cases not easy to apply and can create environmental harm. In this study, we use a different approach where the mowing of saltcedar is timed according to the trend of evapotranspiration (ET) rates. The approach suppresses saltcedar growth, reduces ET loss, allows native vegetation to flourish, and eventually creates a healthy and diverse plant community in riparian areas. In an experimental study from 2010–2013, saltcedar was managed by mowing in a managed riparian area in New Mexico, USA. The timing of mowing was based on the observation of ET rates which were measured using the eddy covariance method. Normalized Difference Vegetation Index (NDVI) was calculated using Landsat imagery to observe any changes in vegetation of saltcedar before and after mowing and its correlation with ET. During the four years of measurement, it was observed that the timing of mowing led to a suppression of saltcedar, allowing the undergrowth of low water-consuming native grasses and other shrubs to thrive. Nonlinear mixed effects models of years of evapotranspiration during the season showed a significant reduction in ET in 2013 compared to the baseline year of 2010 across the growing stages, especially stage 2 (intercept of −2.0871 with p < 0.001). A reduction in ET of 32% from 1209 mm to 818 mm (difference of 391 mm) was observed between 2010 and 2013. This study showed that the best time to suppress saltcedar and allow native plants to reestablish, is to mow it before it breaks dormancy, at the peak and late parts of the growing season. Mowing can be discontinued once the native plants have been established.

Multivariate regression trees as an “explainable machine learning” approach to explore relationships between hydroclimatic characteristics and agricultural and hydrological drought severity: case of study Cesar River basin

Abstract. The typical drivers of drought events are lower than normal precipitation and/or higher than normal evaporation. The region's characteristics may enhance or alleviate the severity of these events. Evaluating the combined effect of the multiple factors influencing droughts requires innovative approaches. This study applies hydrological modelling and a machine learning tool to assess the relationship between hydroclimatic characteristics and the severity of agricultural and hydrological droughts. The Soil Water Assessment Tool (SWAT) is used for hydrological modelling. Model outputs, soil moisture and streamflow, are used to calculate two drought indices, namely the Soil Moisture Deficit Index and the Standardized Streamflow Index. Then, drought indices are utilised to identify the agricultural and hydrological drought events during the analysis period, and the index categories are employed to describe their severity. Finally, the multivariate regression tree technique is applied to assess the relationship between hydroclimatic characteristics and the severity of agricultural and hydrological droughts. Our research indicates that multiple parameters influence the severity of agricultural and hydrological droughts in the Cesar River basin. The upper part of the river valley is very susceptible to agricultural and hydrological drought. Precipitation shortfalls and high potential evapotranspiration drive severe agricultural drought, whereas limited precipitation influences severe hydrological drought. In the middle part of the river, inadequate rainfall partitioning and an unbalanced water cycle that favours water loss through evapotranspiration and limits percolation cause severe agricultural and hydrological drought conditions. Finally, droughts are moderate in the basin's southern part (Zapatosa marsh and the Serranía del Perijá foothills). Moderate sensitivity to agricultural and hydrological droughts is related to the capacity of the subbasins to retain water, which lowers evapotranspiration losses and promotes percolation. Results show that the presented methodology, combining hydrological modelling and a machine learning tool, provides valuable information about the interplay between the hydroclimatic factors that influence drought severity in the Cesar River basin.

Evapotranspiration and groundwater inputs control the timing of diel cycling of stream drying during low-flow periods

Geologic, geomorphic, and climatic factors have been hypothesized to influence where streams dry, but hydrologists struggle to explain the temporal drivers of drying. Few hydrologists have isolated the role that vegetation plays in controlling the timing and location of stream drying in headwater streams. We present a distributed, fine-scale water balance through the seasonal recession and onset of stream drying by combining spatiotemporal observations and modeling of flow presence/absence, evapotranspiration, and groundwater inputs. Surface flow presence/absence was collected at fine spatial (~80 m) and temporal (15-min) scales at 25 locations in a headwater stream in southwestern Idaho, USA. Evapotranspiration losses were modeled at the same locations using the Simultaneous Heat and Water (SHAW) model. Groundwater inputs were estimated at four of the locations using a mixing model approach. In addition, we compared high-frequency, fine-resolution riparian normalized vegetation difference index (NDVI) with stream flow status. We found that the stream wetted and dried on a daily basis before seasonally drying, and daily drying occurred when evapotranspiration outputs exceeded groundwater inputs, typically during the hours of peak evapotranspiration. Riparian NDVI decreased when the stream dried, with a ~2-week lag between stream drying and response. Stream diel drying cycles reflect the groundwater and evapotranspiration balance, and riparian NDVI may improve stream drying predictions for groundwater-supported headwater streams.

Groundwater Flow Modeling of A Microwatershed using Visual Modflow Flex

The present study attempts to make a simulation of groundwater flow modeling in Chikkodi micro-watershed Belagavi (District), Karnataka. A two-layer conceptualization and the three-dimensional groundwater flow model are primarily underlain by weathered basalt and fractured basalt. The first layer weathered zone is 30m from the ground surface and the second layer fractured zone is 80m below the ground surface spread over 20 rows and 20 columns. The cell height is 674m and the cell width is 440m. The work described here built a groundwater flow model in the micro-watershed using Visual MODFLOW Flex. The steady-state groundwater flow model was then numerically projected in April 2020 using seventeen observation wells using the present stress levels. The model aims to quantify input and output stresses and pinpoint the basin's overstressed regions. The water budget analysis estimates that evapotranspiration loss makes up 56.54% of the basin's total groundwater recharge while overall groundwater leaks from river systems are 28.72%. The findings indicated that the southern section of the basin is undergoing severe aquifer stress as a result of river overflow and evapotranspiration. To improve groundwater levels, it is suggested that artificial recharge structures should be developed in and near Chikkodi village at appropriate sites. The trial-and-error approach was used to assess the sensitivity of the calibrated model, and it was discovered that the model is extremely sensitive to changes in hydraulic conductivity and recharge levels. Model performance is excellent, with R2, RMSE, and NRMSE values of 0.97, 5.34, and 13.23% of the assessing criteria.

Field Study to Evaluate Water Loss in the Irrigation Canals of Middle Egypt: A Case Study of the Al Maanna Canal and Its Branches, Assiut Governorate

Egyptian policymakers and researchers have been working to address the challenge of bridging the gap between limited water resources and the growing population’s needs for agricultural and food production. The National Great Project for Lining and Rehabilitation of All Open Canals of the Irrigation Network aims to reduce irrigation water losses through seepage, evaporation, and evapotranspiration. This study evaluated water losses from the Al Maanna canal network in the Assiut governorate, Middle Egypt, using empirical formulas and field ponding methods. The results show the Moleth–Worth formula was more compatible with field measurements, with estimated seepage losses of 2.07 and 2.20 million m3/month, respectively. Moreover, maximum evaporation and evapotranspiration losses were 0.086 and 1.133 million m3/month, respectively. Consequently, total water losses from the Al Maanna canal are estimated to be 3.42 million m3/month, accounting for 13.63% of the total discharge. After canal rehabilitation, evaporation and evapotranspiration losses significantly decreased, while seepage losses were lowered to 0.472 million m3/month, as estimated using the field ponding method. Hence, lining the Al Maanna canal network could reduce water losses by 84%, promoting lining processes that yield significant benefits such as moral, cultural, and environmental benefits. This approach outweighs implementation expenses and ensures a sustainable water supply.

Optimal Determination and Dynamic Control Analysis of the Graded and Staged Drought Limit Water Level of Typical Plateau Lakes

The technical research on determining the drought limit water level can be used as an important basis for starting the emergency response of drought resistance in the basin and guiding the drought resistance scheduling of water conservancy projects. When the concept of drought limit water level was first proposed, the main research object was reservoirs, and the method for determining the lake drought limit water level was not established. Referring to the calculation method of reservoir drought limit water level, the drought limit water level is used as a single warning indicator throughout the year, which lacks graded and staged standards, and also lacks rationality and effectiveness in practical application. Therefore, this article has improved the concept of lake drought limit water level (flow). Under different degrees of drought and water use patterns during the drought period, combined with the characteristics of lake water inflow, considering the factors such as ecology, water supply, and demand, lake inflow, evapotranspiration loss, a graded and staged standard of lake drought limit water level has been developed. For different types of lakes, a general method for determining the lake’s graded and staged drought limit water level has been established. The SCSSA-Elman neural network is used to construct the medium and long-term water inflow prediction model for lakes, and the calculation results of this model are used for the warning and dynamic control analysis of the lake drought limit water level. The application of this method has the characteristics of strong applicability and high reliability. Finally, the determination method and dynamic control method of the lake’s graded and staged drought limit water level have been successfully applied at Dianchi Lake in Yunnan.

Cover crop water consumption: Analysing performance of the agrometeorological model for the calculation of actual evapotranspiration (AMBAV) in a container experiment

AbstractDue to anthropogenic climate change, cover crop water consumption in winter could potentially increase drought stress for a succeeding crop. Simulation of cover crop evapotranspiration (ET) losses could be a tool for farmers to make smart management decisions. In Germany, the model AMBAV is used by the German Meteorological Service (DWD) to advise farmers in irrigation management. We compared measured ET of phacelia (Phacelia tanacetifolia), oilseed radish (Raphanus sativus var. oleiformis) and white mustard (Sinapis alba) cultivated in a container experiment with simulated data and conducted a sensitivity analysis to identify the meteorological and crop‐specific parameters, which had the strongest effect on simulated ET. In general, measured ET exceeded simulated ET. Different statistical criteria showed that AMBAV performed best for the simulation of evaporation from a bare soil surface. Model performance was also strongly influenced by the irrigation regime in the container experiment. However, the sensitivity analysis showed that changes in irrigation hardly influenced simulated ET. We recommend optimization of the model for irrigated agriculture. Furthermore, we identified temperature and humidity as the most important meteorological and leaf area index as the most important crop‐specific parameter for ET simulations with AMBAV. Since farmers' management decisions depend on the accuracy of ET simulations, they should be aware that even small regional deviations of meteorological conditions and soil cover can significantly affect model predictions.

Modelling the impacts of climate change and management options on sustainable groundwater use in an irrigated agriculture landscape

Declining groundwater resources are a big concern for irrigated agriculture worldwide. This study investigated the causes of declining groundwater and how future climate and management measures impact the groundwater resource in Bangladesh. A conceptual hydrological model (NAM) was used to quantify catchment runoff, groundwater recharge and evapotranspiration loss and a hydraulic model (MIKE11) was used to quantify changes in river flow. The models were calibrated using observed water level, discharge, groundwater level (GWL) and actual evapotranspiration (ET). The modelling encompassed five contrasting climate scenarios of rainfall and potential evapotranspiration (PET) and a management scenario of additional surface water irrigation. The results show that GWL is declining across 16 administrative districts in the northwest region of Bangladesh. On average, the annual decline varies from 20 to 30 mm except for two southern districts where the annual decline was more than 80 mm. Declining rainfall and increasing use of groundwater for irrigation were the principal causes of declining GWL across the region. Under the climate change scenarios, modelled groundwater conditions improve due to increased rainfall. The increase in river water extraction for irrigation also produced positive outcomes for GWL (i.e., lessening the declining rate).

Estimating Evapotranspiration for Irrigation Scheduling by Using Atmometers

High-value crops were commodities that were planted in upland production areas and they were known as short-duration crops. On the other hand, if there is no basis for irrigation scheduling other than soil characteristics and plant reaction to low water consumption, results in losses. The main objectives of the study were to evaluate the depth of water for irrigation based on Atmometer reading, assess the growth and yield of organically grown eggplant, wax pepper, and tomato at a different level using drip irrigation water, and to evaluate the cost and economic returns of organically grown high-value crops. The study was conducted at BPSU Bangkal, Abucay, Bataan (N 14°46’ East 120°30’) with a total area of 240 m2 where the three crops were planted equally at three replications. The total rainfall depth at BPSU-AWS Station for October 2021 to November 2022 was 2614.6 mm during the two-season study period. There were three crops raised (eggplant, wax pepper, and tomato). The dripper irrigation system was used to supplement the irrigation water and foliar organic fertilizers. Supplemented water was d on the evapotranspiration loss. Three treatments were subjected for verification (T1 – Irrigate up to 80% of Atmometer reading, T2 - Irrigate up to 100% of Atmometer Reading, and T3 – Irrigate up to 120% of Atmometer. The eggplant of Treatment 1 had the best in terms of weight per fruit (106.0 grams), Treatment 2 was the tallest (74.5 cm), and Treatment 3 had the best harvest (458 pcs). Eggplant does not require enough water for production as long as supplemented even 30% of its evapotranspiration loss. Treatment 2 of Wax Pepper had 7.5 grams per fruit and also exhibited the most number of fruit harvested. Wax Pepper should be supplemented with 50% of its evapotranspiration loss. Treatment 2 of tomatoes had the most in terms of weight per fruit (50.1 grams), tallest among treatments (45.5 cm), and the most number of fruits harvested. Tomatoes should be supplemented with 50% of their evapotranspiration loss. Maximum crop production would attain when evapotranspiration loss should be supplemented at 50% to 100%. More than that was a loss.

Inferences of Groundwater Response to Projected Hydroclimatic Changes in North Florida

Discerning anthropogenic stressors on groundwater is critical for climate change adaptation to reduce risks and increase resiliency. Long-term groundwater level trends are forecasted and examined at three sites in North Florida using a large ensemble of Global Climate Model (GCM) projections under low and medium emission scenarios. The forecasts indicate groundwater levels are likely to decline from 2020 to 2099. However, the declines are expected to accelerate after 2040s, reaching critical levels by the end of this century. Pumping impact constitutes 10% to 45% of future declines but is amplified by enhanced drought. Examination of distinct influence of rainfall, evapotranspiration (ET), and groundwater pumping on future trends shows highly divergent groundwater response to projected hydroclimatic changes. The future long-term rainfall trend may lead to rising groundwater levels, which may be overshadowed by heightened ET loss driven by climate change and increased groundwater pumping, causing steep declines. This study also reveals poor performance of predictions driven by GCM projections in replicating the timing of high and low levels at the sites influenced by Florida’s peninsular climate due to the limitation of downscaling and bias-correction to capture oscillations in climate cycles driving hydrologic memory. However, groundwater levels are predicted well by a few GCMs at one site influenced primarily by continental climate. Additionally, a multidecadal harmonic analysis exposes presence of centennial periodicity in groundwater levels, which opens a new perspective in the understanding of climate change impacts on groundwater resources. Further investigation is needed to better understand the effect of centennial cycles on future groundwater levels and how these cycles can be incorporated into the downscaling methods. Hence, GCM-based forecasts are recommended to be cautiously utilized for groundwater resource planning when they significantly depart from historical long-term cyclic patterns.

Moisture changes in a mountain–basin system since the last deglaciation revealed by the pollen record of Genggahai Lake, northeastern Qinghai-Tibetan Plateau

Asia’s mountainous arid and semiarid regions feature forests in wet high-mountain areas and grasslands/deserts in dry basins. Assessing changes in millennial-scale effective moisture in mountain–basin systems can provide a valuable reference for understanding how climate change and human activities affect terrestrial water resources and drylands. Here, a continuous pollen record from Genggahai Lake on the northeastern Qinghai-Tibetan Plateau exhibited detailed changes in regional vegetation and effective moisture since ∼ 15.3 ka. The pollen sequence suggests that steppe vegetation developed in the basin and that sparse forest vegetation developed in the surrounding mountain areas during 15.3–11.7 ka and 6.3–0 ka, and that desert steppe vegetation developed in the basin and denser forest vegetation developed in the surrounding mountain areas during 11.7–6.3 ka. Based on comparison of regional palaeoclimatic records, the pollen assemblage results suggest antiphase moisture changes between mountains and the basin and imply that the low Artemisia/Chenopodiaceae (A/C) ratio during 11.7–6.3 ka in the basin likely indicates that the low effective moisture conditions likely resulted from the high permeability of loose and porous sediments and the high evaporation in the basin induced by high summer solar insolation. In contrast, the high A/C ratio during 15.3–11.7 ka and 6.3–0 ka indicates a high level of effective moisture during these periods, possibly in response to less evapotranspiration loss in the basin caused by the strong water-binding capacity of palaeosols, ameliorated vegetation conditions, and low summer solar insolation. Our results also suggest that both climatic conditions and anthropogenic activities may have altered the natural vegetation in the late Holocene and that change in the percentage of tree pollen from Genggahai Lake were synchronous with changes in the intensity of the Indian summer monsoon.

Water competition among the coexisting Platycladus orientalis, Prunus davidiana and Medicago sativa in a semi-arid agroforestry system

Agroforestry has been widely used for the ecological restoration construction of semi-arid regions of the Chinese Loess Plateau. Investigating plant water sources is crucial for understanding the key ecohydrological processes of plant root water uptake and the water relations between coexisting plants. Clarifying the plant water use strategies can help to assess the sustainability of the vegetation restoration in agroforestry systems and provide references for the vegetation management. Thus, we investigated the water use characteristics of plants in an agroforestry system consisting of Platycladus orientalis, Prunus davidiana and Medicago sativa. The δD and δ18O of plant stem water and soil water in the 0–300 cm layer were measured. The MixSIAR model and proportional similarity (PS) were used to quantify the proportion of soil water absorbed by the plants in each layer and the hydrological niche overlap of plants. The results showed that the combined effects of rainfall recharge and evapotranspiration (ET) loss resulted in a decrease in soil water content (SWC) for the agroforestry system with increasing soil depth, and the SWC of the deep layer (80–300 cm) had minor variability (6.1–7.1%) throughout the study period. During the study period, due to the deep soil desiccation, P. orientalis, P. davidiana and M. sativa mainly utilized water from shallow (0–80 cm) soil layers, with a contribution rate of 65.4 ± 8.3%, 64.9 ± 7.7% and 73.0 ± 0.2%, respectively. The three coexisting plants relied on the unstable shallow soil water (recharged by rainfall) while the water use proportion of the deep soil layer was consistently low. This implies that the three plants were less resistant to drought stress, thus posing a threat to the stability and sustainability of the agroforestry system. Moreover, even in July and September with the high SWC in agroforestry, the partitioning of soil water among the three coexisting plants did not increase with increased ET loss. The three coexisting plants showed strong competition for soil water use, as indicated by the high values (0.69–0.97) of PS. Overall, the hydrological niche overlap of the coexisting plants in the agroforestry system resulted in low ecosystem stability. Density reduction or selection of suitable species is required to achieve sustainable vegetation restoration.

Soil–vegetation moisture capacitor maintains dry season vegetation productivity over India

India receives more than 70% of its annual rainfall in the summer monsoon from June to September. The rainfall is scanty and scattered for the rest of the year. Combining satellite data and model simulations, we show that the soil-vegetation continuum works as a natural capacitor of water, storing the monsoon pulse and releasing the moisture to the atmosphere through evapotranspiration over approximately 135 days when the moisture supply from precipitation is less than the evapotranspiration losses. The total Gross Primary Productivity of vegetation in India during the capacitor period accounts for almost 35% of the total annual GPP value. It primarily depends on the soil moisture at the beginning of the period, a measure of moisture capacitance of soil, with a correlation of 0.6. Given that India is the second largest contributor to recent global greening, its soil-vegetation water capacitance plays a significant role in the global carbon balance.

Poyen’s Fuzzy Logic Controlled Automatic Irrigation (FCAI): Precision Irrigation Scheduling Scheme

Water wastage is a grave problem in irrigation due to outdated methods. This work illustrates how a well-structured fuzzy rule base can eliminate the issue and utilize water at an optimized level. Poyen’s fuzzy logic controlled automatic irrigation (Poyen’s FCAI) efficiently manages the water requirement needs in irrigation processes considering the evapotranspiration (ET) loss and cultivating conditions. Poyen’s FCAI essentially comprises two modules, the wireless sensor network (WSN) and information processing module to perform the assigned task effectively and efficiently. The wireless sensor unit (WSU) accumulates the necessary data, determines the ET loss, and runs the decision logic before conveying it to the execution unit, i.e., the wireless information processing unit (WIPU). The WIPU executes the decision by manipulating the water delivery system, ensuring that the field receives the optimum volume of water. This article illustrates the fuzzy model with simulation output. The model is field-tested with and without the control action over two seasons and in adjacent plots. The results show promising improvements in both water management and crop yield due to more accurate conditions. Hence, we obtain a superior automatic irrigation prototype model for all soil types, across different growth stages, and for all crops with an exhaustive lookup table in place.

Prediction of Flood Discharge Using Hybrid PSO-SVM Algorithm in Barak River Basin

A crucial necessity in integrated water resource management is flood forecasting. Climate forecasts, specifically flood prediction, comprise multifaceted tasks as they are dependant on several parameters for predicting the dependant variable, which varies from time to time. Calculation of these parameters also changes with geographical location. From the time when Artificial Intelligence was first introduced to the field of hydrological modelling and prediction, it has produced enormous attention in research aspects for additional developments to hydrology. This study investigates the usability of support vector machine (SVM), back propagation neural network (BPNN), and integration of SVM with particle swarm optimization (PSO-SVM) models for flood forecasting. Performance of SVM solely depends on correct assortment of parameters. So, PSO method is employed in selecting SVM parameters. Monthly river flow discharge for a period of 1969 - 2018 of BP ghat and Fulertal gauging sites from Barak River flowing through Barak valley in Assam, India were used. For obtaining optimum results, different input combinations of Precipitation (Pt), temperature (Tt), solar radiation (Sr), humidity (Ht), evapotranspiration loss (El) were assessed. The model results were compared utilizing coefficient of determination (R2) root mean squared error (RMSE), and Nash–Sutcliffe coefficient (NSE). The most important results are highlighted below.•First, the inclusion of five meteorological parameters improved the forecasting accuracy of the hybrid model.•Second, model comparison specifies that hybrid PSO-SVM model executed superior performance with RMSE- 0.04962 and NSE- 0.99334 compared to BPNN and SVM models for monthly flood discharge forecasting.•Third, applied optimization algorithm has easy implementation, simple theory, and high computational efficacy.Results revealed that PSO-SVM could be utilised as an improved alternate method for flood forecasting as it provided a higher degree of reliability and accurateness.