Water Availability Index Research Articles

High-resolution Standardized Precipitation Evapotranspiration Index (SPEI) reveals trends in drought and vegetation water availability in China

Understanding vegetation water availability can be important for managing vegetation and combating climate change. Changes in vegetation water availability throughout China remains poorly understood, especially at a high spatial resolution. Standardized Precipitation Evapotranspiration Index (SPEI) is an ideal water availability index for assessing the spatiotemporal characteristics of drought and investigating the vegetation-water availability relationship. However, no high-resolution and long-term SPEI datasets over China are available. To fill this gap, we developed a new model based on machine learning to obtain high-resolution (1 km) SPEI data by combining climate variables with topographical and geographical features. Here, we analyzed the long-term drought over the past century (1901–2020) and vegetation-water availability relationship in the past two decades (2000–2020). The century-long drought trend analyses indicated an overall drying trend across China with increasing drought frequency, duration, and severity during the past century. We found that drought events in 1901–1961 showed a larger increase than that in 1961–2020, with the Tibetan Plateau showing a significant drying trend during 1901–1960 but a wetting trend during 1961–2020. There were 13.90% and 28.21% of vegetation in China showing water deficit and water surplus respectively during 2000–2020. The water deficit area significantly shrank from 2000 to 2020 across China, which is dominated by the significant decrease in water deficit areas in South China. Among temperature, precipitation, and vegetation abundance (LAI), temperature is the most important factor for the vegetation-water availability dynamics in China over the past two decades, with high temperature contributing to water deficit. Our findings are important for water and vegetation management under a warming climate.

Projected impact of solar radiation modification geoengineering on water deficit risk over major Central African river basins

Abstract The economy of Central African countries strongly depends on rain-fed agriculture and hydropower generation. However, most countries in this subregion do not yet have the irrigation technologies that are already applied in many more advanced nations, which further exposes them to the serious risk of severe drought caused by global warming. This study investigates the potential impact of solar radiation modification (SRM) geoengineering on the water availability over the four major river basins that cross most of Central African countries (i.e. Niger Basin, Lake Chad Basin, Cameroon Atlantic Basin (CAB) and Congo Basin). For this purpose a potential water availability index was computed based on an ensemble-mean simulations carried out in the framework of Phase 6 of the Geoengineering Model Intercomparison Project considering two SRM simulation experiments: the stratospheric sulphate aerosol injection (G6sulfur) and the global solar dimming (G6solar). The climate change simulation results in a robust decreases by up to 60% in water availability, most pronounced over the CAB under the high radiative forcing scenario. Therefore, in a business-as-usual world, the reduction in water availability combined with the rapid population growth expected by 2050 in the studied subregion, could result in a significant water deficit over Central African countries towards the end of the 21st century. This water deficit could affect all activities that depend on water resources, such as water supply, agriculture and hydropower generation. Furthermore, the results also show that SRM methods have the potential to significantly reduce this deficit by increasing water availability (as compared to climate change) by up to 50% over the affected river basins, with a more accentuated increase found in the CAB when the global solar dimming is applied. These results suggest good possibilities of adaptation for populations living in the geographical areas of these river basins.

Semi-arid rather than arid regions of China deserve the priority in drought mitigation efforts

The integration of drought assessment, mitigation priority analysis and mitigation measures development is a forward-looking strategy to achieve water resources allocation, implement anti-drought techniques and formulate corresponding mitigation measures strategies. However, since most drought indices cannot be based on surface water-balance to estimate water demand for drought recovery, there is a gap between drought assessment and proactive drought mitigation. Here, we established the Standardized Water Availability Index (taking water yield as surface water deficit/surplus) to identify hydrological drought, and further use it to determine the water demand for hydrological drought mitigation. On that basis, a comprehensive framework, integrating with drought assessment-resilience-recovery and water scarcity stress, was proposed to investigate the hydrological drought mitigation priority for basins in different climate regions in China. The results show that non-humid river basins have greater water scarcity stress, lower resilience to hydrological drought, but less water demand for hydrological drought mitigation (3 mm ∼ 7 mm in mild drought, 5 mm ∼ 14 mm in moderate drought, 7 mm ∼ 21 mm in severe drought). In contrast, humid river basins have greater water demand for hydrological drought mitigation (15 mm ∼ 49 mm in mild drought, 27 mm ∼ 93 mm in moderate drought, 32 mm ∼ 119 mm in severe drought), but higher resilience to hydrological drought. The densely populated semi-arid river basins in China should be given priority attention in mitigating hydrological drought on account of their greatest water scarcity stress, lower drought resilience, and less water demand for drought mitigation. This work highlights the complexity of the hydrological drought mitigation, and our findings can help stakeholders to make precise drought mitigation measures and adapt drought-relative water management.

Vegetation greening accelerated hydrological drought in two-thirds of river basins over China

Although the vegetation-greening-induced water supply reduction has been widely recognized, little is known about the impacts of vegetation greening on hydrological drought. Here Standardized Water Availability Index (SWAI, based on surface water-balance), driven by evapotranspiration (ET, with vegetation dynamics), was developed to quantify the impacts of vegetation greening on hydrological drought at multiple timescales over China from 1982 to 2015. The ET with vegetation dynamics was modeled by the improved PT-JPL model, and was validated with in-situ observed data from 8 flux tower sites and 4 on-site field experiments (covered with 12 different land-cover types in China). SWAI was also validated with monthly runoff records (from 59 gauging stations over different climatic regimes in China), and proved to effectively capture the response of water surplus/deficit to vegetation dynamics. Results reveal that percentage drought-affected areas increased (increased by 2 % to 9 %) and drought intensity enhanced in two-thirds of Chinese river basins due to vegetation greening. Moreover, in nearly half of the river basins in China, drought duration increased by 0.035–0.131 months, and drought frequency increased by 0.016–0.085 months/34-year. Hydrological drought accelerated by vegetation greening mainly occurred in arid and semi-arid river basins (water-limited areas), while it was not obvious in humid and sub-humid river basins due to limited energy for ET in these areas. Our work and findings provide new insights for understanding the vegetation-induced water resource shortage and have potential applications for government and water managers to timely monitor and assess the balance between ecological restoration and water resources.

Analysis of Rainwater Availability and Water Requirements in the Amarasi District Area Kupang Regency

The hydrological conditions of the Amarasi District, Kupang Regency have 3-4 wet months and 8-9 dry months according to Oldeman’s classification. Annual rainfall in the last ten years shows the lowest rainfall was 1,461mm and the highest was 2,688mm, the average annual rainfall was 1,859mm. The Amarasi region is included in zones D and E of the Oldeman climate classification. The practice of utilizing limited water resources by planting fodder crops in the form of legumes and grasses as well as food crops in integrated dry land agriculture has been carried out by the Amarasi community. This research examines the availability and demand for domestic, agricultural and livestock water and will produce an availability index as the carrying capacity of regional water availability. The method used to calculate the availability of water originating from rain is runoff analysis based on weighted coefficients for each land use, then analyzed in a monthly series and compared with the level of water demand for each use. Domestic water needs, livestock drinking and irrigation follow SNI 19-6728.1.2002. Then the analysis results are interpreted with tables and time series graphs. The research results show the following time series of water availability: January: 44,626,635.13m3; February: 31,210,646.01m3; March : 20,050,098.53m3; April: 11,726,074.47m3; May : 3,023,180.66m3; June: 1,747,689.52m3; July : 973,284.18m3; August : 168,880.36m3; September: 1,026,614.82m3. October 2,846,522.91m3; November 10,713,903.37m3; and December: 26,871,976.23m3. The amount of water demand in the time series is as follows: January: 1,929,491.70m3; February: 1,391,817.98m3; March: 1,697,543.42m3; April: 781,567.95m3; May : 883,736.22m3; June: 755,911.95m3; July : 284,777.42m3; August : 384,569.42m3; September: 387,871.95m3. October 355,448.02m3; November 3,242,283.15m3; and December: 2,631,159.26m3. Water availability index: January: 4.32 (good), February: 4.46 (good), March: 8.47 (good), April: 6.67 (good), May: 29.23 (slight critical), June: 43.25 (mild critical), July: 29.26 (mild critical), August: 227.27 (bad/severe critical), September: 37.78 (mild critical), October 12.49 (good), November: 30.26 (mild critical) and December 9.79 (good).

Study of ecosystem service functions in typical receiving areas of the South-to-North Water Diversion Central Route based on a set of long time series.

Hebi is located in the northern part of China's Henan Province and is a typical receiving area for China's South-to-North Water Diversion Project. The assessment of habitat quality and water yield over a long time series is important for evaluating the stability of ecosystem services in Hebi and other receiving areas and for maintaining ecological security and promoting sustainable development. This paper aims to evaluate and dynamically analyse habitat quality and water yield in Hebi, and analyses the characteristics of changes in spatial and temporal patterns of land cover types, habitat quality and water yield in Hebi over the past 20 years, using 2000, 2005, 2010, 2015 and 2020 as horizontal years. The results indicate that: (1) During the study period, the overall land use type in Hebi City has been constantly changing, with the most significant conversion from arable land to other land types; combined with its landscape pattern index, Hebi City has a general characteristic of significant landscape fragmentation and complexity in land use. (2) Habitat quality in Hebi shows an overall trend towards better development, with water availability decreasing and then increasing; the zoning of ecosystem services in Hebi is divided into three classes: superior, good and general, with the area covered by the superior and general classes expanding year by year. (3) Correlation analysis by SPSS software shows that the correlation between habitat quality and landscape pattern index is greater than the correlation between habitat quality and climate change. Additionally, the correlation between water availability and climate change is greater than the correlation between water availability and landscape pattern index.

Spatio-temporal patterns and control mechanism of the ecosystem carbon use efficiency across the Mongolian Plateau

Carbon use efficiency (CUE) is a crucial parameter that reflects the carbon storage within ecosystems, providing insight into the potential for carbon sequestration at the ecosystem scale and its feedback on climate change. The Mongolian Plateau exemplifies an arid and semi-arid region with a delicate ecological environment that displays heightened sensitivity to global climate change. Understanding the variation and control of CUE is critical for assessing regional carbon. However, few studies have focused on the interaction of factors influencing CUE; furthermore, how CUE responds to climate change and anthropogenic activities remains unclear. Here, we aimed to investigate spatiotemporal patterns and their control mechanisms by generating CUE data based on multi-source remote sensing data. CUE demonstrated a slow downward trend from 2000 to 2018, with higher values in relatively dry–cool regions and lower values in relatively humid–warm regions. Furthermore, CUE values were ranked by biome as follows: grassland > sandy vegetation > cropland > shrubs > forest, driven by climate characteristics, vegetation coverage, water stress, stand age, and management practices. Additionally, climatic factors affected CUE more than the soil variables, except for alpine meadows. The climate factors of precipitation (PPT), index of water availability (IWA) (QPPT = 0.487, QIWA = 0.444), and soil factors, e.g., pH and soil organic content (SOC) (QPH = 0.397, QSOC = 0.372), had the greatest influence on CUE. Finally, most two explanatory factors interacted to effectively enhance the explanation of CUE; the synergy of the IWA and PPT contributed the most to CUE (QIWA∩PPT = 0.604). Moreover, the joint effect of climate change and anthropogenic activities was identified as the major contributor (68 %) to the decline in CUE within this region. This study presents compelling evidence highlighting the importance of considering climate change and anthropogenic disturbances in ecosystem management and conservation efforts in arid and semi-arid regions.

Twenty years of net photosynthesis, climatic and anthropic factors from biomes of Bahia State, Brazil

The Brazilian biomes Atlantic Forest, Cerrado, and Caatinga are considered biodiversity hotspots in the world and are fundamental to the global and regional carbon balance. However, deforestation and/or burning and changes in land use and land cover have contributed to the increase of carbon dioxide (CO2) in the atmosphere as well as the consequent greenhouse effect and global warming. Net photosynthesis is a natural CO2 levels regulation process in the atmosphere and it is influenced by vegetation composition, climatic and anthropogenic factors. In this sense, this study aimed to evaluate the Net Photosynthesis (PSN) in 20 years in the Brazilian biomes Atlantic Forest, Cerrado, and Caatinga, to verify the monthly correlation between PSN and intervening factors, such as climatic variables and burned areas, as well as to determine trends of increase and decrease over the years of all variables studied. The study was based on eight-day MOD17 Net Photosynthesis images and the results showed that monthly PSN in the three biomes is more positively correlated (p-value < 0.05) with actual evapotranspiration together with water availability index and has more negative correlation (p-value < 0.05) with land surface temperature. Spatially, during the following 20 years, the Mann-Kendal test showed an PSN decreasing trend in the Atlantic Forest biome and an increasing trend in the Cerrado biome. These trends observed in the mentioned biomes are related to the advance of agriculture and cattle ranching. Finally, this study provides relevant information on net photosynthesis and interference of climatic and anthropogenic factors, being essential for monitoring and formulation of policies that stimulate carbon absorption in biomes.

Land Surfaces at the Tipping‐Point for Water and Energy Balance Coupling

AbstractThe surface water and energy balances can be coupled or uncoupled depending on whether the evaporation regime is water‐limited or energy‐limited. As the landscape loses soil moisture during drydowns, a transition between the regimes may occur, which signifies a nonlinear change in water‐energy‐carbon coupling. Regions that switch often between these two regimes, that is, are dominated by neither regime, are particularly vulnerable to climate variability and change. To robustly identify these tipping points, we identify drydown events based on global soil moisture data sets from remote sensing. The event identification does not rely on precipitation information and is robust with respect to measurement noise. Then, the soil moisture thresholds delineating the evaporation regime transitions are determined by Sequential Monte Carlo Sampling and a two‐stage parametrization strategy. Based on the estimated soil moisture thresholds across the globe, we estimate observation‐based water availability indices which quantify the nonlinear controls of soil moisture on evaporation. This framework is tested and applied globally using Soil Moisture Active Passive soil moisture retrievals. Combined with a new tippling‐point metric that describes the frequency of evaporation regime transitions, we identify regions that switch often between different evaporation regimes at the global scale. Given unit shifts in soil moisture, these regions will experience the most change in how their surface water and energy are coupled.

A combined GIS and remote sensing approach for monitoring climate change-related land degradation to support landscape preservation and planning tools: the Basilicata case study

Monitoring landscapes in times of climate change patterns is a crucial issue, moreover, in the analyzed Mediterranean area, one of the major global candidates to develop land degradation stresses and consequential desertification phenomena. The research presented here is developed in the Mediterranean Basin, specifically in the Basilicata Region (southern Italy). The region is characterized by a very long history of intensive anthropization endowed by the high diversity of relatively geologically young soil types that consequentially created a vastity of spatial mosaics, which contributed to the composition of its archeolandscapes and endorsed some specific characteristics of the Mediterranean region, that evolved to respond to the human impact, including grazing, cultivation, and fires. Those key elements lead to the crucial issues of the region investigated here as soil erosion, salinization, loss of organic carbon, loss of biodiversity, and landslides, which together with deforestations, depopulation, and wildfires, define the exact framework of degradation and marginality. The evaluation of the sensitivity to degradation was performed (i) firstly at the regional scale, through a MEDALUS (Kosmas et al. 1999) approach, by implementing 6 main indicators (Soil Quality Index, Climate Quality Index, Vegetation Quality Index, Management Quality Index, Landslide Risk Index, Water Availability Index), and (ii) secondly at the mid-regional scale, through remote sensing by evaluation of the NDVI differencing thresholds in time intervals, covering a 20 years’ time span going from 2000 to 2020. The study helped to define the in-progress land degradation trends and scenarios of the region, which must be the evidence-based foundation of integrated landscape planning strategies in marginal territories, implemented through a Decision Support System (DSS) based both on ecological, climate-adaptive, and environmental indicators, and on social, cultural, and economic development co-creation strategies.

Artificial intelligence to predict West Nile virus outbreaks with eco-climatic drivers.

SummaryBackgroundIn Europe, the frequency, intensity, and geographic range of West Nile virus (WNV)-outbreaks have increased over the past decade, with a 7.2-fold increase in 2018 compared to 2017, and a markedly expanded geographic area compared to 2010. The reasons for this increase and range expansion remain largely unknown due to the complexity of the transmission pathways and underlying disease drivers. In a first, we use advanced artificial intelligence to disentangle the contribution of eco-climatic drivers to WNV-outbreaks across Europe using decade-long (2010-2019) data at high spatial resolution.MethodsWe use a high-performance machine learning classifier, XGBoost (eXtreme gradient boosting) combined with state-of-the-art XAI (eXplainable artificial intelligence) methodology to describe the predictive ability and contribution of different drivers of the emergence and transmission of WNV-outbreaks in Europe, respectively.FindingsOur model, trained on 2010-2017 data achieved an AUC (area under the receiver operating characteristic curve) score of 0.97 and 0.93 when tested with 2018 and 2019 data, respectively, showing a high discriminatory power to classify a WNV-endemic area. Overall, positive summer/spring temperatures anomalies, lower water availability index (NDWI), and drier winter conditions were found to be the main determinants of WNV-outbreaks across Europe. The climate trends of the preceding year in combination with eco-climatic predictors of the first half of the year provided a robust predictive ability of the entire transmission season ahead of time. For the extraordinary 2018 outbreak year, relatively higher spring temperatures and the abundance of Culex mosquitoes were the strongest predictors, in addition to past climatic trends.InterpretationOur AI-based framework can be deployed to trigger rapid and timely alerts for active surveillance and vector control measures in order to intercept an imminent WNV-outbreak in Europe.FundingThe work was partially funded by the Swedish Research Council FORMAS for the project ARBOPREVENT (grant agreement 2018-05973).

A copula incorporated cellular automata module for modeling the spatial distribution of oasis recovered by ecological water diversion: An application to the Qingtu Oasis in Shiyang River basin, China

Assessing the impact of ecological water diversion on oasis restoration is critical for water resources and environmental management in arid inland basins. This study proposed a copula incorporated cellular automata (CA) module for modeling the oasis’s spatial distribution driven by ecological water diversion. Given the effects of groundwater depth and community expansion on oasis evolution, a water availability index and a neighbor vegetation index were proposed. These two indices were joint using the Clayton copula function, producing a vegetation suitability index that quantified vegetation growth’s habitat quality and provided the CA module’s basis to identify cellular categories. The CA module was integrated into a previously developed conceptual lumped ecohydrological model (CLEM), resulting in an improved CA-CLEM that outputted groundwater depth, oasis area, oasis NDVI, and oasis distribution data. The CLEM provided the oasis area changes for the CA module, which specified the spatial distribution of these changes. The CA-CLEM had a simple structure, low computation cost, and good performance, indicated by the application in the Shiyang River basin in Northwest China. Results show that an ecological water diversion of 30 million m3, with an average groundwater depth of 2.95 m, an oasis area of 25 km2, and an oasis NDVI of 0.36, would successfully recover the terminal Qingtu Oasis in 2020. The oasis distribution and its dynamic evolution processes were irregular because of the spatial heterogeneity of vegetation habitat suitability. The present Qingtu Oasis was fragile, and its sustainability relied on ecological water diversion. The reduction in water diversion would cause water table decline, oasis area shrinkage, vegetation degradation, and oasis fragmentation. The CA-CLEM combined with scenario analysis provides practical and reliable implications for managers and policymakers to improve ecological water diversion strategies.

Markov Analysis of Water Discharge as an Indicator of Surface Water Security of the Bandung Basin

Water security is the fulfillment of access to adequate and sustainable water needs (quantity and quality) for the growth of human and ecosystem life and the ability to reduce risks associated with water. By knowing the water security of an area, efforts to conserve, utilize, control destructive force, develop information systems and participate in the community can be assessed to what extent and how the management has been carried out. The purpose of this research is to formulate the amount of water availability per capita (quantity) of surface water and to determine the quantity of the worst water quality at a critical time (the worst quantity) to be used as a reference in determining the amount of water resistance for development. The only observed water quality was the BOD (Biological Oxygen Demand) organic pollutant value in the dry year in the dry season using the Markov Chain Method. Water security in the Bandung Basin is currently classified as bad (rare) because the water availability index figures only indicate 174 m3 per capita per year (quantity). Meanwhile, data on the quality value of BOD (Biological Oxygen Demand) pollutants in dry years (R5) of 129 mg/l and very dry years (R10) of 112 mg/l which has also exceeded the class I quality standard of PP No. 22/2021 (&gt; 2 mg/l) regarding water quality management and pollution control which is designated for raw water needs drinking water. Changing water use patterns and promoting effective implementation of integrated water resources management are essential strategies for increasing water security in Indonesia.

GIS-Based Land Suitability Classification for Wheat Cultivation Using Fuzzy Set Model

In terms of food safety, it is important to use the lands correctly in agricultural production. In this study, potential crop suitability classes for wheat cultivation were created by using the fuzzy model and GIS together. Spatial and spectral factors considered as model inputs were separated four main groups, such as soil (drainage, depth, texture, CaCO3, stoniness, pH, organic matter, salinity, ESP), topography (slope), water availability (irrigation) and vegetation indices (NDVI). Criterion maps were standardized with the fuzzy membership model. Analytical Hierarchy Process was used to determine the weights of the factors. The vegetation change between years in the study area was determined by using NDVI values obtained from Landsat satellite images. In addition, the effect of temporal difference on land use and land suitability was evaluated. Land suitability index was created in GIS environment by weighted linear combination method and divided into four main suitability classes. The results with the Fuzzy method showed 9.7% (805 ha) of the study area as highly suitable for wheat, 46.5% (3868 ha) as medium suitable, 27.6% (2297 ha) as marginally suitable and 16.2% (1350 ha) as unsuitable. According to these classes, highly suitable and medium suitable classes are the areas that should be evaluated primarily in agricultural production. The Fuzzy model and GIS integration can be effectively used to identify priority areas for crop cultivation and sustainable land use management.

Analysis of water availability and planting index in dams in Bedadung watershed

The increasing population causes the government to work to improve food security. One of the policies adopted is to increase the productivity of agricultural land. Increased productivity of agricultural land can be increased by increasing the crop index. Planting index is the total area for crops per planting season for a year. In this case support from irrigation, the sector is very important. From the preliminary survey in the study area, we found some damage to the irrigation assets that might reduce the performance of the assets which caused the crop index to be lower than the maximum crop index (300%). This study aims to (1) calculate the availability of irrigation water, (2) calculate the crop index, and (3) analyze the potential increase in the crop index and the expansion of agricultural land. The results showed that there were 80 dams (44.4%) experienced abundant water but had a crop index value of less than 300%. Thus, the service area of 80 dams can be increased the value of the planting index to 300%. While there are 100 dams (55.6%) experiencing water shortages. In this case, the recommendations that can be given are providing water supply through the construction of a reservoir or changing the pattern of planting paddy - paddy - paddy into paddy - palawija -palawija. We conclude that water delivery in the Bedadung Watershed area is not effective. This can be caused by damage to irrigation assets. Therefore, a recommendation that can be given for further research is the effect of irrigation asset performance on irrigation services.

Cropping calendar analysis for dry season 2020 in Indonesia

Indonesia has various rainfall characteristics that result variations in the initial planting time and cropping patterns. The Integrated Cropping Calendar Information System is a guidance for planting rice, maize, and soybean at the right time with sufficient water availability conditions. This paper aimed to analyse the planting schedule and potential planting area of rice, maize, and soybeans in the dry season 2020 at 7,062 sub-districts in Indonesia. Input data were rainfall prediction, spatial-based ETP, soil water availability, wetland area, and rice cropping index. The stages were the analyses on rainfall, calculating soil water balance, and determining potential planting area. The results illustrated that the mean rainfall intensity and rainfall intensities of <60 and 200-300 mm mo−1 were predicted as the widest rainfall coverages in April-June and July-September. The potential planting areas for rice, maize, and soybean were 5,259,661, 1,263,575, and 559,545 ha, respectively. Rice and maize initial planting periods were mainly in April II-II, while soybean in July III-August. Potential planting area for rice can be expanded to become 6,674,428 ha by applying additional water supply from alternative sources at the potential areas of maize and soybean.

Soil water deficit as a tool to measure water stress and inform silvicultural management in the Cape Forest Regions, South Africa

An understanding of variations in water availability to plantation forests on a spatial and temporal scale is essential when designing risk averse and site-specific silvicultural management regimes. Various indices of site water availability were compared to each other and to an independent, unbiased estimate of stand productivity potential, namely site index, across the Tsitsikamma, Knysna and Boland forestry regions of South Africa. This was done to find the balance between water availability indices requiring intensive data inputs (that may be very accurate) and indices with lower input data requirements (but may sacrifice some accuracy). The following indices of water availability (in order from low to higher input data requirements) were tested: Mean Annual Precipitation (MAP); Aridity Index (AI), i.e., MAP as a fraction of mean annual potential evapotranspiration (Ep); Moisture Growing Season (MGS), i.e., the Julian days where long-term MAP exceeds 0.3 times Ep; Water Deficit (WD), an estimate based on a rudimentary water balance with relatively low data inputs. The first three estimates use only climatic variables while the WD incorporates soil water storage capacity to run a water balance calculation. Results showed that both regional climatic variability and soil properties significantly affected the level of water availability, and hence also the potential productivity of pine stands. The shallow and sandy soils from the Knysna and Boland regions exhibited rapid water depletion during periods of decreased precipitation and seasonal shifts, however, the large WD’s (up to 345 mm year-1) observed in several of these sites rapidly changed to surplus values following only one month of high precipitation. Sites from the Tsitsikamma region had significantly larger water retention capabilities and this was attributed to the regional soil properties and climatic conditions. Temporal variations in the WD were also quantified. The WD estimates correlated significantly (r = -0.80, p<0.001) to the respective site indices from sites across all regions. These results underscore the importance of soil water availability on plantation productivity, especially in moderately dry regions or in areas with either shallow soils or a seasonal rainfall pattern. We conclude that the WD is a fairly accurate estimate of site-specific water availability with relatively low data requirements. The WD estimates are far superior to currently used indices of water availability in Southern Africa and has data input requirements that are currently readily available for most plantation forest sites.

Assessment of Water Availability and Scarcity Based on Hydrologic Components in an Irrigated Agricultural Watershed Using SWAT

AbstractThis study assesses the water availability and the water scarcity based on the hydrologic behavior under different weather conditions and crop coverages in an irrigated agricultural area of Rincon Valley in New Mexico using the SWAT (Soil and Water Assessment Tool) model. Two spatial crop coverages included normal (2008) and dry (2011) years with 14 different crop sets for each year. The SWAT was applied to generate the five essential indicators (surface flow, evapotranspiration, soil water, groundwater recharge, and irrigation water) to evaluate the integrated water availability based on hydrologic response units (HRUs) along with the Arrey Canal to supply irrigation water in the crop areas. The water availability index scores (0–1 range with 1 being the most available and 0 the least available) of alfalfa, corn, cotton, and pecans were 0.21, 0.56, 0.91, and 0.20, respectively, in the normal year and 0.16, 0.78, 0.88, and 0.24, respectively, in the dry year. In the dry year, water scarcity values were high in mostly alfalfa areas, whereas cotton areas have mostly no stress with good water availability. The major water users of crops, ranked in order, were alfalfa, pecans, cotton, and corn. During the dry year, water availability showed to be balanced in terms of water supply and demand by controlling crop patterns from reducing alfalfa acreage by 12% and increasing cotton acreage by 13%.

Long-Term Trends in 20-Day Cumulative Precipitation for Residential Rainwater Harvesting in Poland

Rainwater harvesting (RWH) for domestic uses is widely regarded as an economic and ecological solution in water conservation and storm management programs. This paper aims at evaluating long-term trends in 20-day cumulative rainfall periods per year in Poland, for assessing its impact on the design and operation conditions for RWH systems and resource availability. The time-series employed corresponds to a set of 50-year long time-series of rainfall (from 1970 to 2019) recorded at 19 synoptic meteorological stations scattered across Poland, one of the European countries with the lowest water availability index. The methods employed for assessing trends were the Mann–Kendall test (M–K) and the Sen’s slope estimator. Most of the datasets exhibit stationary behaviour during the 50-year long period, however, statistically significant downward trends were detected for precipitations in Wrocław and Opole. The findings of this study are valuable assets for integrated water management and sustainable planning in Poland.

Spatial variations and controls of carbon use efficiency in China\u2019s terrestrial ecosystems

Carbon use efficiency (CUE), one of the most important eco-physiological parameters, represents the capacity of plants to transform carbon into new biomass. Understanding the variations and controls of CUE is crucial for regional carbon assessment. Here, we used 15-years of continuous remote sensing data to examine the variations of CUE across broad geographic and climatic gradients in China. The results showed that the vegetation CUE was averaged to 0.54 ± 0.11 with minor interannual variation. However, the CUE greatly varied with geographic gradients and ecosystem types. Forests have a lower CUE than grasslands and croplands. Evergreen needleleaf forests have a higher CUE than other forest types. Climate factors (mean annual temperature (MAT), precipitation (MAP) and the index of water availability (IWA)) dominantly regulated the spatial variations of CUE. The CUE exhibited a linear decrease with enhanced MAT and MAP and a parabolic response to the IWA. Furthermore, the responses of CUE to environmental change varied with individual ecosystem type. In contrast, precipitation exerted strong control on CUE in grassland, while in forest and cropland, the CUE was mainly controlled by the available water. This study identifies the variations and response of CUE to environmental drivers in China, which will be valuable for the regional assessment of carbon cycling dynamics under future climate change.