In order to estimate water use, water requirements and carbon sequestration of tropical plantation systems such as rubber it is adamant to have accurate information on leaf area development of the plantation as the main determinant of evapotranspiration. Literature commonly suggests a number of different methods on how to obtain leaf area index (LAI) information from tree plantation systems. Methods include destructive measurements of leaf area at peak LAI, indirect methods such as gap fraction methods (i.e. Hemiview and LAI 2000) and radiation interception methods (i.e. SunScan) or litter fall traps. Published values for peak LAI in rubber plantation differ widely and show no clear trend to be explained by management practices or the influence of local climate patterns. This study compares four methods for determining LAI of rubber plantations of different ages in Xishuangbanna, Yunnan, PR China. We have tested indirect measurement techniques such as light absorption and gap fraction measurements and hemispherical image analysis against litter fall data in order to obtain insights into the reliability of these measuring techniques for the use in tropical tree plantation systems. In addition, we have included data from destructive harvesting as a comparison. The results presented here clearly showed that there was no consistent agreement between the different measurements. Site, time of the day and incoming radiation all had a significant effect on the results depending on the devices used. This leaves us with the conclusion that the integration of published data on LAI in rubber into broad ranging assessments is very difficult to accomplish as the accuracy of the measurements seems to be very sensitive to a number of factors. This diminishes the usefulness of literature data in estimating evapotranspiration from rubber plantations and the induced environmental effects, both on local as well as regional levels. © 2017 Elsevier Ltd
Tag: Evapotranspiration
CMIP6-based global estimates of future aridity index and potential evapotranspiration for 2021-2060
The Future_Global_AI_PET Database offers high-resolution global estimates (30 arc-seconds) of potential evapotranspiration (PET) and aridity index (AI), derived from 22 CMIP6 Earth System Models. It covers two historical periods (1960–1990; 1970–2000) and two future periods (2021–2041; 2041–2060), analyzing climate trends across four shared socio-economic pathways (SSPs). The dataset includes three multimodel ensemble averages (All, Majority Consensus, High Risk) to account for different levels of climate model uncertainty. A methodological overview, geospatial implementation details, and technical evaluation accompany the database. Historical data validation compared results with weather station data (PET: r² = 0.72; AI: r² = 0.91) and the CRU_TS v4.04 dataset (PET: r² = 0.67; AI: r² = 0.80). Given the anticipated climate shifts, this database serves as a valuable resource for scientific and practical applications, offering insights into predicted eco-hydrological and terrestrial ecosystem impacts.
Water balance and maize yield following improved sesbania fallow in eastern Zambia
Sesbania [Sesbania sesban (L.) Merr.] fallows are being promoted as a means for replenishing soil fertility in N-depleted soils of small-scale, resource-poor farmers in southern Africa. Knowledge of soil water distribution in the soil profile and water balance under proposed systems is important for knowing the long-term implications of the systems at plot, field and watershed levels. Soil water balance was quantified for maize (Zea mays L.) following 2-year sesbania fallow and in continuous maize with and without fertilizer during 1998–1999 and 1999–2000 at Chipata in eastern Zambia. Sesbania fallow increased grain yield and dry matter production of subsequent maize per unit amount of water used. Average maize grain yields following sesbania fallow, and in continuous maize with and without fertilizer were 3, 6 and 1 Mg ha1 with corresponding water use efficiencies of 4.3, 8.8 and 1.7 kg mm1 ha1, respectively. Sesbania fallow increased the soil-water storage in the soil profile and drainage below the maximum crop root zone compared with the conventionally tilled non-fertilized maize. However, sesbania fallow did not significantly affect the seasonal crop water use, mainly because rainfall during both the years of the study was above the normal seasonal water requirements of maize (400 to 600 mm). Besides improving grain yields of maize in rotation, sesbania fallows have the potential to recharge the subsoil water through increased subsurface drainage and increase nitrate leaching below the crop root zone in excess rainfall seasons.
Agroforestry and watershed functions of tropical land use mosaics
An ‘ecohydrology’ approach involves more than a focus on the degree of forest cover in the upper watersheds, as the quantity, timing and quality of water flows is determined by the land cover and land use in the whole landscape. We discuss the different perceptions that still exist on the special relations between ‘forest’ and ‘watershed functions’ and consider which specific function is relevant for whom. Land use change can modify the evapotranspiration and hence the total water yield of a catchment, but also the pathways that water will take and hence the amount of soil particles, nutrients, agrochemicals and (in arid regions) salt that it will carry downstream. Evenness of river flow is influenced by the infiltration rates in the landscape if small areas are considered. Partial spatial independence of rainfall becomes a dominant explanation of ‘evenness of flow’ when larger areas are considered, reducing the relative importance of land use. Agroforestry options for the riparian zone can have a major impact on the water quality and evenness of flow perceived downstream, probably exceeding the importance of forest cover in upper watersheds.
Light interception and evaporation in hedgerow agroforestry systems
Quantifying water lost through evaporation and transpiration in a cropping system is an important tool in adapting a system for semi-arid conditions. During two cropping seasons in eastern Kenya, light interception and soil water content were measured in several different cropping systems: monocultures of cowpea (Vigna unguiculata (L.) Walp.), maize (Zea mays cv. Katumani), Senna spectabilis cv. Embu managed as a hedge, and hedge intercrops of cowpea and maize. These systems differed with respect to plant population density, maximum light interception (44–75%) and canopy height (0.5–2.0 m). Parameters in the EPIC model for leaf area development were derived from periodically-measured light interception in the different systems. Daily light interception predicted from the leaf area was used to partition potential evapotranspiration into potential evaporation and potential transpiration. A simple water balance model was used to predict actual transpiration and actual soil evaporation. Predicted values of water loss during the two seasons correlated closely with measured values (r2 = 0.85 and 0.91; slope = 1.00 and 1.01). In both seasons, the model predicted that soil evaporation comprised approximately half (42–58%) of the estimated evapotranspiration. This study suggests that evapotranspiration can be predicted for a variety of cropping systems when light interception measurements are used in conjunction with a simple model of plant water uptake. It also demonstrates the difficulty of maximizing plant water use in agroforestry systems in semi-arid environments when the canopies of both annual crops and hedges develop simultaneously.
Sensitivity of groundwater recharge under irrigated agriculture to changes in climate, CO2 concentrations and canopy structure
Estimating groundwater recharge in response to increased atmospheric CO2 concentration and climate change is critical for future management of agricultural water resources in arid or semi-arid regions. Based on climate projections from the Intergovernmental Panel on Climate Change, this study quantified groundwater recharge under irrigated agriculture in response to variations of atmospheric CO2 concentrations (550 and 970 ppm) and average daily temperature (+1.1 and +6.4 C compared to current conditions). HYDRUS 1D, a model used to simulate water movement in unsaturated, partially saturated, or fully saturated porous media, was used to simulate the impact of climate change on vadose zone hydrologic processes and groundwater recharge for three typical crop sites (alfalfa, almonds and tomatoes) in the San Joaquin watershed in California. Plant growth with the consideration of elevated atmospheric CO2 concentration was simulated using the heat unit theory. A modified version of the Penman-Monteith equation was used to account for the effects of elevated atmospheric CO2 concentration. Irrigation amount and timing was based on crop potential evapotranspiration. The results of this study suggest that increases in atmospheric CO2 and average daily temperature may have significant effects on groundwater recharge. Increasing temperature caused a temporal shift in plant growth patterns and redistributed evapotranspiration and irrigation water use earlier in the growing season resulting in a decrease in groundwater recharge under alfalfa and almonds and an increase under tomatoes. Elevating atmospheric CO2 concentrations generally decreased groundwater recharge for all crops due to decreased evapotranspiration resulting in decreased irrigation water use. Increasing average daily temperature by 1.1 and 6.4 C and atmospheric CO2 concentration to 550 and 970 ppm led to a decrease in cumulative groundwater recharge for most scenarios. Overall, the results indicate that groundwater recharge may be very sensitive to potential future climate changes.
Seasonal evapotranspiration signatures under a changing landscape and ecosystem management in Nigeria: implications for agriculture and food security
Low crop productivity is a general problem facing most farming systems in sub-Saharan Africa (SSA). These low yields are pronounced in grain legumes and are often associated with declining soil fertility and reduced N2-fixation due to biological and environmental factors. Unfortunately, the majority of African small farmers are now unable to afford the high mineral fertilizer prices. More than 75% of the fertilizers used in Africa are imported, putting pressure on foreign exchange. Low cost and sustainable technical solutions compatible with the socioeconomic conditions of small farmers are needed to solve soil fertility problems. Biological nitrogen fixation (BNF), a key source of N for farmers using little or no fertilizer, constitutes one of the potential solutions and plays a key role in sustainable grain legumes (e.g., soybean) production. Given the high cost of fertilizer in Africa and the limited market infrastructure for farm inputs, current research and extension efforts have been directed to integrated nutrient management, in which legumes play a crucial role. Inoculation with compatible and appropriate rhizobia may be necessary where a low population of native rhizobial strains predominates and is one of the solutions which grain legume farmers can use to optimize yields. It is critical for sustained yield in farmlands deficient in native rhizobia and where N supply limits production. Research on use of Rhizobium inoculants for production of grain legumes showed it is a cheaper and usually more effective agronomic practice for ensuring adequate N nutrition of legumes, compared with the application of N fertilizer. Here, we review past and ongoing interventions in Rhizobium inoculation (with special reference to soybean) in the farming systems of SSA with a view to understanding the best way to effectively advise on future investments to enhance production and adoption of BNF and inoculant technologies in SSA. The major findings are: (1) complete absence of or very weak institutions, policy and budgetary support for biotechnology research and lack of its integration into wider agricultural and overall development objectives in SSA, (2) limited knowledge of inoculation responses of both promiscuous and specifically nodulating soybean varieties as well as the other factors that inhibit BNF, hence a weak basis for decisionmaking on biotechnology issues in SSA, (3) limited capacity and lack of sustainable investment, (4) poorly developed marketing channels and infrastructure, and limited involvement of the private sector in the distribution of inoculants, and (5) limited farmer awareness about and access to (much more than price) inoculants. The lessons learned include the need: (1) to increase investment in Rhizobium inoculation technology development, and strengthen policy and institutional support, (2) for public private partnership in the development, deployment and dissemination of BNF technologies, (3) to develop effective BNF dissemination strategies (including participatory approach) to reach farmers, (4) for greater emphasis on capacity building along the BNF value chain, and (5) for partnership between universities in SSA and those in the North on BNF research.
Hyperspectral narrowband and multispectral broadband indices for remote sensing of crop evapotranspiration and its components (transpiration and soil evaporation)
Evapotranspiration (ET) is an important component of micro- and macro-scale climatic processes. In agriculture, estimates of ET are frequently used to monitor droughts, schedule irrigation, and assess crop water productivity over large areas. Currently, in situ measurements of ET are difficult to scale up for regional applications, so remote sensing technology has been increasingly used to estimate crop ET. Ratio-based vegetation indices retrieved from optical remote sensing, like the Normalized Difference Vegetation Index (NDVI), Soil Adjusted Vegetation Index, and Enhanced Vegetation Index are critical components of these models, particularly for the partitioning of ET into transpiration and soil evaporation. These indices have their limitations, however, and can induce large model bias and error. In this study, micrometeorological and spectroradiometric data collected over two growing seasons in cotton, maize, and rice fields in the Central Valley of California were used to identify spectral wavelengths from 428 to 2295 nm that produced the highest correlation to and lowest error with ET, transpiration, and soil evaporation. The analysis was performed with hyperspectral narrowbands (HNBs) at 10 nm intervals and multispectral broadbands (MSBBs) commonly retrieved by Earth observation platforms. The study revealed that (1) HNB indices consistently explained more variability in ET (ΔR2 = 0.12), transpiration (ΔR2 = 0.17), and soil evaporation (ΔR2 = 0.14) than MSBB indices; (2) the relationship between transpiration using the ratio-based index most commonly used for ET modeling, NDVI, was strong (R2 = 0.51), but the hyperspectral equivalent was superior (R2 = 0.68); and (3) soil evaporation was not estimated well using ratio-based indices from the literature (highest R2 = 0.37), but could be after further evaluation, using ratio-based indices centered on 743 and 953 nm (R2 = 0.72) or 428 and 1518 nm (R2 = 0.69).
Who or what makes rainfall? Relational and instrumental paradigms for human impacts on atmospheric water cycling
Human impacts on water cycles (HIWC) can include modification of rainfall. Spatial and temporal variation in rainfall, with implications for ‘water security’, has been attributed to multiple causal pathways, with different options for human agency. Ten historical paradigms of the cause of rainfall imply shifts from ‘nature controlling humans’ to ‘human control over nature’ and ‘human control over other humans’. Paradigm shifts have consequences for human efforts, interacting with social–ecological systems, to appease spirits, please rainmakers, expose ‘rainfakers’, protect forest, plant trees, reduce greenhouse gas emissions, apply cloud seeding, or declare rainfall modification an illegitimate tool in warfare. The ‘instrumental’ and ‘relational’ values of atmospheric water cycling depend on cognitive paradigms of rainfall causation as represented in local, public/policy, or science-based ecological knowledge. The paradigms suggest a wide range of human decision points that require reinterpretation of rationality for any paradigm shift, as happened with the forest–rainfall linkages.
Version 3 of the Global Aridity Index and Potential Evapotranspiration Database
The “Global Aridity Index and Potential Evapotranspiration Database – Version 3” (Global-AI_PET_v3) provides high-resolution (30 arc-seconds) global hydro-climatic data averaged (1970–2000) monthly and yearly, based upon the FAO Penman-Monteith Reference Evapotranspiration (ET0) equation. An overview of the methods used to implement the Penman-Monteith equation geospatially and a technical evaluation of the results is provided. Results were compared for technical validation with weather station data from the FAO “CLIMWAT 2.0 for CROPWAT” (ET0: r2 = 0.85; AI: r2 = 0.90) and the U.K. “Climate Research Unit: Time Series v 4.04” (ET0: r2 = 0.89; AI: r2 = 0.83), while showing significant differences to an earlier version of the database. The current version of the Global-AI_PET_v3 supersedes previous versions, showing a higher correlation to real world weather station data. Developed using the generally agreed upon standard methodology for estimation of reference ET0, this database and notably, the accompanying source code, provide a robust tool for a variety of scientific applications in an era of rapidly changing climatic conditions.