Parametric calibration of the Hargreaves–Samani equation for use at new locations

The Hargreaves–Samani (HS) evapotranspiration equation is very useful for the on‐site irrigation management in data‐short situations such as small and midsize farms and landscaped areas. Although much work has been performed to improve the precision of the evapotranspiration (ET_o) estimates for use at new locations, the results have not been consistent and many have not been confirmed by other works. The purpose of this study was to review and to evaluate the seven most promising parameters used for the calibration of the HS evapotranspiration equation, using two different regions: California and Bolivia. The results of this study show that annual correlations between HS and Penman–Monteith can be misleading because the correlation is poor in the humid months and improves progressively along the dry season until the first rains. The average monthly wind speed can be used for both spatial and seasonal calibration of the HS equation, especially during the irrigation season. Elevation and precipitation can be used to calibrate the HS equation when no reference ET_o values are available at nearby stations. The monthly value of K_T calculated from solar radiation follows a parabolic function along the year and should not be used for improving the estimates of the HS equation because the clearness index produces better results than actual solar radiation measurements. The results also indicate that the use of distance to coast, temperature range and temperature parameter does not improve the precision of the HS equation. Copyright © 2012 John Wiley & Sons, Ltd.     

Regional impacts of climate change on irrigation water demands

This paper presents an approach to model the expected impacts of climate change on irrigation water demand in a reservoir command area. A statistical downscaling model and an evapotranspiration model are used with a general circulation model (GCM) output to predict the anticipated change in the monthly irrigation water requirement of a crop. Specifically, we quantify the likely changes in irrigation water demands at a location in the command area, as a response to the projected changes in precipitation and evapotranspiration at that location. Statistical downscaling with a canonical correlation analysis is carried out to develop the future scenarios of meteorological variables (rainfall, relative humidity (RH), wind speed (U₂), radiation, maximum (Tmax) and minimum (Tmin) temperatures) starting with simulations provided by a GCM for a specified emission scenario. The medium resolution Model for Interdisciplinary Research on Climate GCM is used with the A1B scenario, to assess the likely changes in irrigation demands for paddy, sugarcane, permanent garden and semidry crops over the command area of Bhadra reservoir, India. Results from the downscaling model suggest that the monthly rainfall is likely to increase in the reservoir command area. RH, Tmax and Tmin are also projected to increase with small changes in U₂. Consequently, the reference evapotranspiration, modeled by the Penman–Monteith equation, is predicted to increase. The irrigation requirements are assessed on monthly scale at nine selected locations encompassing the Bhadra reservoir command area. The irrigation requirements are projected to increase, in most cases, suggesting that the effect of projected increase in rainfall on the irrigation demands is offset by the effect due to projected increase/change in other meteorological variables (viz., Tmax and Tmin, solar radiation, RH and U₂). The irrigation demand assessment study carried out at a river basin will be useful for future irrigation management systems. Copyright © 2012 John Wiley & Sons, Ltd.     

Potential influence of climate change on ecosystems within the Boreal Plains of Alberta

Ecosystems within the subhumid Boreal Plains of Northern Alberta host ecologically and commercially significant habitat and natural resources. However, these ecosystems exist under a delicate hydrologic balance that may be upset as the climate warms by 2 to 5 °C over the next century. In this study, numerical simulations were used to predict climate change impacts at a catchment composed of a mosaic of Boreal Plains ecosystems including a small pond, peatlands with sparse black spruce, and hillslopes with predominantly aspen forests. Simulations were conducted with a fully integrated groundwater–surface water code using a 2‐D model previously calibrated to a decade of hydrologic data that included a range in climatic conditions. Projections from 13 climate change scenarios were simulated from 2011 to 2090 and compared to a base case scenario that assumed no climate change. Results indicate peatland water levels may decline by up to 1 m; however, sensitivity simulations indicate that the decline in water levels may be moderated by several feedback mechanisms that restrict evaporative losses and moderate water level changes. In contrast, higher evapotranspiration losses from the aspen hillslopes are predicted to result in near‐surface soils becoming increasingly drier. Thus, the aspen may frequently be water stressed and increasingly susceptible to secondary maladies such as pests and disease. Reduced pond water levels are also predicted with the development of frequent ephemeral conditions in warmer and drier scenarios. Concurrent decreases in stream flow may further impact downstream ecosystems. Further research into the regional health and sustainability of Boreal Plains ecosystems is warranted and could benefit from the development of improved numerical tools capable of extending the processes considered.     

Modelling and analysis of the impact of irrigation on local arid climate over northwest China

This study focuses on how irrigation processes affect local climate over arid areas. The chosen study area is northwest China, a typical arid region where three dominant land‐use types are irrigated cropland, grassland, and desert. Observational analysis indicates that the highest precipitation, the coolest surface temperatures, and the slowest warming trend are seen over irrigated cropland from 1979 to 2005. The single column atmospheric model (SCAM), developed by the National Center for Atmospheric Research (NCAR), was used to investigate and better understand the differences in long‐term climate conditions and change over the above three land‐use types. The results indicate that local climate conditions are predominantly controlled by large‐scale forcing in this arid region and that local land surface forcing related to vegetation cover change and irrigation processes also has a significant impact. This study strongly suggests that a realistic climate forecast for this region can be achieved only with both accurate large‐scale and local climate forcing. The irrigated cropland of the region generates stronger evaporation that cools the surface and slows the warming trend more than does the evaporation from the natural grassland and desert. Stronger evaporation also significantly increases precipitation, potentially alleviating the stress of irrigation demands in arid regions. A series of sensitivity SCAM simulations indicate that a drier and warmer climate occurs with decreasing vegetation cover in the irrigated cropland region. Copyright © 2011 John Wiley & Sons, Ltd.     

Influence of land evapotranspiration on climate variations

A coupled numerical model of the global atmosphere with a qualified biosphere (GOALS/LASG) has been used to assess the nature of the physical mechanisms for land-atmosphere interactions, and the impacts of the Asian/North American land-surface evapotranspiration on the regional and global climate. This sensitivity study suggests that the simulated climate would be relatively sensitive to land surface evapotranspiration, especially over the Asian regions. The removal of evapotranspiration in Asia would create a warmer and drier climate to a certain degree. Furthermore, the surface evapotranspiration anomalies would make a substantial contribution to the formation and variation of subtropical anticyclones through the changes in monsoon precipitation and the β -effect, but also make a large contribution to the variations of the atmospheric circulation in the Northern Hemisphere and even the globe. Therefore, besides the traditional perception that we have generally emphasized on the influence of subtropical anticyclones activities on the boreal summer precipitation over the regions of eastern China, the surface evapotranspiration anomalies, however, also have substantial impacts on the subtropical anticyclones through the changes in monsoon precipitation. For this reason, the variation in the internal heating sources of the atmosphere caused by the land surface evapotranspiration and the vapor phase change during the boreal summer is an important external factor forcing the weather and climate.     

Robust inferences on climate change patterns of precipitation extremes in the Iberian Peninsula

This work presents a methodology to make statistical significant and robust inferences on climate change from an ensemble of model simulations. This methodology is used to assess climate change projections of the Iberian daily-total precipitation for a near-future (2021–2050) and a distant-future (2069–2098) climates, relatively to a reference past climate (1961–1990).Climate changes of precipitation spatial patterns are estimated for annual and seasonal values of: (i) total amount of precipitation (PRCTOT), (ii) maximum number of consecutive dry days (CDD), (iii) maximum of total amount of 5-consecutive wet days (Rx5day), and (iv) percentage of total precipitation occurred in days with precipitation above the 95th percentile of the reference climate (R95T). Daily-total data were obtained from the multi-model ensemble of fifteen Regional Climate Model simulations provided by the European project ENSEMBLES. These regional models were driven by boundary conditions imposed by Global Climate Models that ran under the 20C3M conditions from 1961 to 2000, and under the A1B scenario, from 2001 to 2100, defined by the Special Report on Emission Scenarios of the Intergovernmental Panel on Climate Change.Non-parametric statistical methods are used for significant climate change detection: linear trends for the entire period (1961–2098) estimated by the Theil-Sen method with a statistical significance given by the Mann-Kendall test, and climate-median differences between the two future climates and the past climate with a statistical significance given by the Mann-Whitney test. Significant inferences of climate change spatial patterns are made after these non-parametric statistics of the multi-model ensemble median, while the associated uncertainties are quantified by the spread of these statistics across the multi-model ensemble. Significant and robust climate change inferences of the spatial patterns are then obtained by building the climate change patterns using only the grid points where a significant climate change is found with a predefined low uncertainty.Results highlight the importance of taking into account the spread across an ensemble of climate simulations when making inferences on climate change from the ensemble-mean or ensemble-median. This is specially true for climate projections of extreme indices such CDD and R95T. For PRCTOT, a decrease in annual precipitation over the entire peninsula is projected, specially in the north and northwest where it can decrease down to 400 mm by the middle of the 21st century. This decrease is expected to occur throughout the year except in winter. Annual CDD is projected to increase till the middle of the 21st century overall the peninsula, reaching more than three weeks in the southwest. This increase is projected to occur in summer and spring. For Rx5day, a decrease is projected to occur during spring and autumn in the major part of the peninsula, and during summer in northern Iberia. Finally, R95T is projected to decrease around 20% in northern Iberia in summer, and around 15% in the south-southwest in autumn.     

Impact of bushfire and climate variability on streamflow from forested catchments in southeast Australia

Abstract

This paper quantifies the impacts of bushfire and climate variability on streamflow from three southeast Australian catchments where bushfires occurred in February 1983. Three hydrological models (AWRA-L, Xinanjiang and GR4J) were first calibrated against streamflow data from the pre-bushfire period and then used to simulate runoff for the post-bushfire period with the calibrated parameters. The difference in simulated streamflow between pre- and post-bushfire periods provides an estimate of the impact of climate variability on streamflow. The impact of bushfire on streamflow is quantified by removing the climate variability impact from the difference in mean annual observed streamflow between post- and pre-bushfire periods. For the first 15 years after the 1983 bushfires, the results from hydrological models for the three catchments indicate that there is a substantial increase in streamflow; this is attributed to initial decreases in evapotranspiration and soil infiltration rates resulting from the fires, followed by logging activity. After 15 years, streamflow dynamics are more heavily influenced by climate effects, although some impact from fire and logging regeneration may still occur. The results show that hydrological models provide reasonably consistent estimates of bushfire and climate impacts on streamflow for the three catchments. The models can be used to quantify relative contributions of forest disturbance (bushfire, logging and other forest management) and climate variability. The results presented can also help forest managers understand the relationship between bushfire and climate variability impacts on water yield in the context of climate variability.     

Quantifying the impact of climate variables on reference evapotranspiration in Pearl River Basin,China

ABSTRACT

The impact of climate variables on monthly reference evapotranspiration (ET_o) is a critical issue in water resources management and irrigation planning. The spatio-temporal contribution of climate variables to ET_o in the Pearl River Basin (PRB), China, from 1960 to 2016 were calculated based on sensitivity and relative change of each climatic variable. The results show that annual ET_o total decreased by 1.64% and diminished in magnitude from the southeast to the northwest. Sunshine duration, wind speed and relative humidity decreased by 15.5%, 7.4%, and 4.0%, respectively, while average temperature increased by 4.25%. The ET_o showed a positive sensitivity to all variables except relative humidity, which showed a negative sensitivity. Sunshine duration had the highest contribution of ?4.26%, and the overall decrease in ET_o was mainly caused by the declines in sunshine duration and wind speed, which offset the positive impact of rises in average temperature and reduction in relative humidity.     

Validation and calibration of solar radiation equations for estimating daily reference evapotranspiration at cool semi-arid and arid locations

ABSTRACT

In this work, the applicability of 12 solar radiation (R_S) estimation models and their impacts on daily reference evapotranspiration (ET_o) estimates using the Penman‐Monteith FAO-56 (PMF-56) method were tested under cool arid and semi-arid conditions in Iran. The results indicated that the average increase in accuracy of the ET_o estimates by the calibrated R_S models, quantified by the decrease in RMSE, was 2.8% and 6.4% for semi-arid and arid climates, respectively. Mean daily deviations in the estimated ET_o by the calibrated R_S equations in semi-arid climates varied from ?0.283?mm/d^-1 for the Glover‐McCulloch model to 0.080?mm/d for the El-Sebaii model, with an average of ?0.109?mm/d^-1, and in arid climates, they ranged from ?0.522?mm/d^-1 for the Samani model to 0.668?mm/d for the El-Sebaii model, with an average of 0.125?mm/d^-1.

Editor D. Koutsyiannis; Associate editor Not assigned     

Evapotranspiration is resilient in the face of land cover and climate change in a humid temperate catchment

In temperate humid catchments, evapotranspiration returns more than half of the annual precipitation to the atmosphere, thereby determining the balance available to recharge groundwaters and support stream flow and lake levels. Changes in evapotranspiration rates and, therefore, catchment hydrology could be driven by changes in land use or climate. Here, we examine the catchment water balance over the past 50 years for a catchment in southwest Michigan covered by cropland, grassland, forest, and wetlands. Over the study period, about 27% of the catchment has been abandoned from row‐crop agriculture to perennial vegetation and about 20% of the catchment has reverted to deciduous forest, and the climate has warmed by 1.14 °C. Despite these changes in land use, the precipitation and stream discharge, and by inference catchment‐scale evapotranspiration, have been stable over the study period. The remarkably stable rates of evapotranspirative water loss from the catchment across a period of significant land cover change suggest that rainfed annual crops and perennial vegetation do not differ greatly in evapotranspiration rates, and this is supported by measurements of evapotranspiration from various vegetation types based on soil water monitoring in the same catchment. Compensating changes in the other meteorological drivers of evaporative water demand besides air temperature—wind speed, atmospheric humidity, and net radiation—are also possible but cannot be evaluated due to insufficient local data across the 50‐year period. Regardless of the explanation, this study shows that the water balance of this landscape has been resilient in the face of both land cover and climate change over the past 50 years.     

Impacts of climate change on water resources in the Mediterranean Basin: a case study in Catalonia,Spain

Abstract

Most climate change projections show important decreases in water availability in the Mediterranean region by the end of this century. We assess those main climate change impacts on water resources in three medium-sized catchments with varying climatic conditions in northeastern Spain. A combination of hydrological modelling and climate projections with B1 and A2 IPCC emission scenarios is performed to infer future streamflows. The largest reduction (34%) in mean streamflows (for 2076–2100) is expected in the headwaters of the two wettest catchments, while lower decreases (25% of mean value for 2076–2100) are expected in the drier one. In all three catchments, autumn and summer are the seasons with the most notable projected decreases in streamflow, of 50% and 30%, respectively. Thus, ecological flows in the study area might be noticeably influenced by climate change, especially in the headwaters of the wet catchments.     

Sensitivity of hydrological variables to climate change in the Haihe River basin,China

Using the defined sensitivity index, the sensitivity of streamflow, evapotranspiration and soil moisture to climate change was investigated in four catchments in the Haihe River basin. Climate change contained three parts: annual precipitation and temperature change and the change of the percentage of precipitation in the flood season (P_f). With satisfying monthly streamflow simulation using the variable infiltration capacity model, the sensitivity was estimated by the change of simulated hydrological variables with hypothetical climatic scenarios and observed climatic data. The results indicated that (i) the sensitivity of streamflow would increase as precipitation or P_f increased but would decrease as temperature increased; (ii) the sensitivity of evapotranspiration and soil moisture would decrease as precipitation or temperature increased, but it to P_f varied in different catchments; and (iii) hydrological variables were more sensitive to precipitation, followed by P_f, and then temperature. The nonlinear response of streamflow, evapotranspiration and soil moisture to climate change could provide a reference for water resources planning and management under future climate change scenarios in the Haihe River basin. Copyright © 2011 John Wiley & Sons, Ltd.     

Artificial neural network models for estimating regional reference evapotranspiration based on climate factors

Evapotranspiration (ET) is one of the basic components of the hydrologic cycle and is essential for estimating irrigation water requirements. In this study, an artificial neural network (ANN) model for reference evapotranspiration (ET₀) calculation was investigated. ANNs were trained and tested for arid (west), semi‐arid (middle) and sub‐humid (east) areas of the Inner Mongolia district of China. Three or four climate factors, i.e. air temperature (T), relative humidity (RH), wind speed (U) and duration of sunshine (N) from 135 meteorological stations distributed throughout the study area, were used as the inputs of the ANNs. A comparison was conducted between the estimates provided by the ANNs and by multilinear regression (MLR). The results showed that ANNs using the climatic data successfully estimated ET₀ and the ANNs simulated ET₀ better than the MLRs. The ANNs with four inputs were more accurate than those with three inputs. The errors of the ANNs with four inputs were lower (with RMSE of 0·130 mm d^?1, RE of 2·7% and R² of 0·986) in the semi‐arid area than in the other two areas, but the errors of the ANNs with three inputs were lower in the sub‐humid area (with RMSE of 0·21 mm d^?1, RE of 5·2% and R² of 0·961. For the different seasons, the results indicated that the highest errors occurred in September and the lowest in April for the ANNs with four inputs. Similarly, the errors were higher in September for the ANNs with three inputs. Copyright © 2008 John Wiley & Sons, Ltd.     

Climate changes and their impacts on water resources in semiarid regions: a case study of the Wei River basin,China

Understanding the impacts of climate change and human activity on the hydrological processes in river basins is important for maintaining ecosystem integrity and sustaining local economic development. The objective of this study was to evaluate the impact of climate variability and human activity on mean annual flow in the Wei River, the largest tributary of the Yellow River. The nonparametric Mann–Kendall test and wavelet transform were applied to detect the variations of hydrometeorological variables in the semiarid Wei River basin in the northwestern China. The identifications were based on streamflow records from 1958 to 2008 at four hydrological stations as well as precipitation and potential evapotranspiration (PET) data from 21 climate stations. A simple method based on Budyko curve was used to evaluate potential impacts of climate change and human activities on mean annual flow. The results show that annual streamflow decreased because of the reduced precipitation and increased PET at most stations. Both annual and seasonal precipitation and PET demonstrated mixed trends of decreasing and increasing, although significant trends (P < 0.05) were consistently detected in spring and autumn at most stations. Significant periodicities of 0.5 and 1 year (P < 0.05) were examined in all the time series. The spectrum of streamflow at the Huaxian station shows insignificant annual cycle during 1971–1975, 1986–1993 and 1996–2008, which is probably resulted from human activities. Climate variability greatly affected water resources in the Beiluo River, whereas human activities (including soil and water conservation, irrigation, reservoirs construction, etc.) accounted more for the changes of streamflow in the area near the Huaxian station during different periods. The results from this article can be used as a reference for water resources planning and management in the semiarid Wei River basin. Copyright © 2012 John Wiley & Sons, Ltd.     

The effects of climate change on potential groundwater recharge in Great Britain

The predicted increase in mean global temperature due to climate change is expected to affect water availability and, in turn, cause both environmental and societal impacts. To understand the potential impact of climate change on future sustainable water resources, this paper outlines a methodology to quantify the effects of climate change on potential groundwater recharge (or hydrological excess water) for three locations in the north and south of Great Britain. Using results from a stochastic weather generator, actual evapotranspiration and potential groundwater recharge time‐series for the historic baseline 1961–1990 and for a future ‘high’ greenhouse gas emissions scenario for the 2020s, 2050s and 2080s time periods were simulated for Coltishall in East Anglia, Gatwick in southeast England and Paisley in west Scotland. Under the ‘high’ gas emissions scenario, results showed a decrease of 20% in potential groundwater recharge for Coltishall, 40% for Gatwick and 7% for Paisley by the end of this century. The persistence of dry periods is shown to increase for the three sites during the 2050s and 2080s. Gatwick presents the driest conditions, Coltishall the largest variability of wet and dry periods and Paisley little variability. For Paisley, the main effect of climate change is evident during the dry season (April–September), when the potential amount of hydrological excess water decreases by 88% during the 2080s. Overall, it is concluded that future climate may present a decrease in potential groundwater recharge that will increase stress on local and regional groundwater resources that are already under ecosystem and water supply pressures. Copyright © 2007 John Wiley & Sons, Ltd.     

Modelling interannual variations in catchment evapotranspiration considering vegetation and climate seasonality using the Budyko framework

The Budyko framework is an efficient tool for investigating catchment water balance, focusing on the effects of seasonal changes in climate (S) and vegetation cover (M) on catchment evapotranspiration (ET). However, the effects of vegetation seasonality on ET remain largely unknown. The present study explored these effects by modelling interannual variations in ET considering vegetation and climate seasonality using the Budyko framework. Reconstructed 15-day GIMMS NDVI_3g timeseries data from 1982 to 2015 were used to estimate M and extract the relative duration of the vegetation growing season (GL) in the Yellow River Basin (YRB). To characterize S, seasonal variations in precipitation and potential ET were extracted using a Gaussian algorithm. Analysis of the observed datasets for 19 catchments revealed that interannual variation in the catchment parameter ϖ (in Fuh's equation) was significantly and positively correlated with M and GL. Conversely, ϖ was significantly but negatively correlated with S. Furthermore, stepwise linear regression was used to calibrate the empirical formula of ϖ for these three dimensionless parameters. Following validation, based on observations in the remaining 11 catchments, ϖ was integrated into Fuh's equation to accurately estimate annual ET. Over 79% subcatchments showed an upward trend (0.9 mm yr⁻¹), whereas fewer than 21% subcatchments showed a downward trend (−0.5 mm yr⁻¹) across YRB. In the central region of the middle reach, ET increased with increased M, prolonged GL, and decreased S, whereas in the source region of YRB, ET decreased with decreased M and shortened GL. Our study provides an alternative method to estimate interannual ET in ungauged catchments and offers a novel perspective to investigate hydrological responses to vegetation and climate seasonality in the long-term.     

The influence of climate change on suspended sediment transport in Danish rivers

The HIRHAM regional climate model suggests an increase in temperature in Denmark of about 3 °C and an increase in mean annual precipitation of 6–7%, with a larger increase during winter and a decrease during summer between a control period 1961–1990 and scenario period 2071–2100. This change of climate will affect the suspended sediment transport in rivers, directly through erosion processes and increased river discharges and indirectly through changes in land use and land cover. Climate‐change‐induced changes in suspended sediment transport are modelled for five scenarios on the basis of modelled changes in land use/land cover for two Danish river catchments: the alluvial River Ansager and the non‐alluvial River Odense. Mean annual suspended sediment transport is modelled to increase by 17% in the alluvial river and by 27% in the non‐alluvial for steady‐state scenarios. Increases by about 9% in the alluvial river and 24% in the non‐alluvial river were determined for scenarios incorporating a prolonged growing season for catchment vegetation. Shortening of the growing season is found to have little influence on mean annual sediment transport. Mean monthly changes in suspended sediment transport between ? 26% and + 68% are found for comparable suspended sediment transport scenarios between the control and the scenario periods. The suspended sediment transport increases during winter months as a result of the increase in river discharge caused by the increase in precipitation, and decreases during summer and early autumn months. Copyright © 2007 John Wiley & Sons, Ltd.     

Design and testing of a global climate prediction system based on a coupled climate model

A global climate prediction system(PCCSM4) was developed based on the Community Climate System Model, version 4.0, developed by the National Center for Atmospheric Research(NCAR), and an initialization scheme was designed by our group. Thirty-year(1981–2010) one-month-lead retrospective summer climate ensemble predictions were carried out and analyzed. The results showed that PCCSM4 can efficiently capture the main characteristics of JJA mean sea surface temperature(SST), sea level pressure(SLP), and precipitation. The prediction skill for SST is high, especially over the central and eastern Pacific where the influence of El Ni?o-Southern Oscillation(ENSO) is dominant. Temporal correlation coefficients between the predicted Ni?o3.4 index and observed Ni?o3.4 index over the 30 years reach 0.7, exceeding the 99% statistical significance level. The prediction of 500-hPa geopotential height, 850-hPa zonal wind and SLP shows greater skill than for precipitation. Overall, the predictability in PCCSM4 is much higher in the tropics than in global terms, or over East Asia. Furthermore, PCCSM4 can simulate the summer climate in typical ENSO years and the interannual variability of the Asian summer monsoon well. These preliminary results suggest that PCCSM4 can be applied to real-time prediction after further testing and improvement.