scholarly journals Changes in Stream Peak Flow and Regulation in Naoli River Watershed as a Result of Wetland Loss

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Yunlong Yao ◽  
Lei Wang ◽  
Xianguo Lv ◽  
Hongxian Yu ◽  
Guofu Li
Keyword(s):  
Peak Flow ◽  
Daily Rainfall ◽  
Wetland Loss ◽  
Wetland Area ◽  
First Order ◽  
Rate Of Increase ◽  
Increasing Trend ◽  
Exponential Decay Model ◽  
Streamflow Data ◽  
Peak Streamflow

Hydrology helps determine the character of wetlands; wetlands, in turn, regulate water flow, which influences regional hydrology. To understand these dynamics, we studied the Naoli basin where, from 1954 to 2005, intensive marshland cultivation took place, and the watershed’s wetland area declined from94.4×104 ha to17.8×104 ha. More than 80% of the wetland area loss was due to conversion to farmland, especially from 1976 to 1986. The processes of transforming wetlands to cultivated land in the whole Naoli basin and subbasins can be described using a first order exponential decay model. To quantify the effects of wetlands cultivation, we analyzed daily rainfall and streamflow data measured from 1955 to 2005 at two stations (Baoqing Station and Caizuizi Station). We defined a streamflow regulation index (SRI) and applied a Mann-Kendall-Sneyers test to further analyze the data. As the wetland area decreased, the peak streamflow at the Caizuizi station increased, and less precipitation generated heavier peak flows, as the runoff was faster than before. The SRI from 1959 to 2005 showed an increasing trend; the SRI rate of increase was 0.05/10a, demonstrating that the watershed’s regulation of streamflow regulation was declined as the wetlands disappeared.

scholarly journals Modeling and forecasting of rainfall reoccurrence changes using Markov Switching in Iran

2021 ◽  
Vol 3 (8) ◽  
Author(s):  
Majid Javari
Keyword(s):  
Environmental Planning ◽  
Rainfall Variability ◽  
Markov Switching ◽  
Daily Rainfall ◽  
First Order ◽  
Markov Switching Models ◽  
Markov Transition Matrix ◽  
Switching Models ◽  
Markov Transition ◽  
Modeling And Forecasting

AbstractThis paper represents the recurrence (reoccurrence) changes in the rainfall series using Markov Switching models (MSM). The switching employs a dynamic pattern that allows a linear model to be combined with nonlinearity models a discrete structure. The result is the Markov Switching models (MSM) reoccurrence predicting technique. Markov Switching models (MSM) were employed to analyze rainfall reoccurrence with spatiotemporal regime probabilities. In this study, Markov Switching models (MSM) were used based on the simple exogenous probability frame by identifying a first-order Markov process for the regime probabilities. The Markov transition matrix and regime probabilities were used to analyze the rainfall reoccurrence in 167 synoptic and climatology stations. The analysis results show a low distribution from 0.0 to 0.2 (0–20%) per day spatially from selecting stations, probability mean of daily rainfall recurrence is 0.84, and a different distribution based on the second regime was found to be more remarkable to the rainfall variability. The rainfall reoccurrence in daily rainfall was estimated with relatively low variability and strong reoccurrence daily with ranged from 0.851 to 0.995 (85.1–99.5%) per day based on the spatial distribution. The variability analysis of rainfall in the intermediate and long variability and irregular variability patterns would be helpful for the rainfall variability for environmental planning.

scholarly journals Projected Changes in Intense Precipitation over Europe at the Daily and Subdaily Time Scales*

2015 ◽  
Vol 28 (15) ◽  
pp. 6193-6203 ◽  
Author(s):  
Enrico Scoccimarro ◽  
Gabriele Villarini ◽  
Marcello Vichi ◽  
Matteo Zampieri ◽  
Pier Giuseppe Fogli ◽  
...  
Keyword(s):  
Time Scales ◽  
Climate Model ◽  
Daily Rainfall ◽  
Heavy Precipitation ◽  
High Rate ◽  
Intense Precipitation ◽  
Rate Of Increase ◽  
Daily Scale ◽  
Projected Changes ◽  
Precipitation Events

Abstract Heavy precipitation is a major hazard over Europe. It is well established that climate model projections indicate a tendency toward more extreme daily rainfall events. It is still uncertain, however, how this changing intensity translates at the subdaily time scales. The main goal of the present study is to examine possible differences in projected changes in intense precipitation events over Europe at the daily and subdaily (3-hourly) time scales using a state-of-the-science climate model. The focus will be on one representative concentration pathway (RCP8.5), considered as illustrative of a high rate of increase in greenhouse gas concentrations over this century. There are statistically significant differences in intense precipitation projections (up to 40%) when comparing the results at the daily and subdaily time scales. Over northeastern Europe, projected precipitation intensification at the 3-hourly scale is lower than at the daily scale. On the other hand, Spain and the western seaboard exhibit an opposite behavior, with stronger intensification at the 3-hourly scale rather than the daily scale. While the mean properties of the precipitation distributions are independent of the analyzed frequency, projected precipitation intensification exhibits regional differences. This finding has implications for the extrapolation of impacts of intense precipitation events, given the daily time scale at which the analyses are usually performed.

scholarly journals PERKIRAAN PELUANG HUJAN UNTUK MENENTUKAN WAKTU TANAM KAPAS DI NUSA TENGGARA BARAT

2020 ◽  
Vol 9 (2) ◽  
pp. 39
Author(s):  
PRIMA D. RIAJAYA ◽  
F. T. KADARWATI ◽  
MOCH. MACHFUD
Keyword(s):  
Gossypium Hirsutum ◽  
Daily Rainfall ◽  
Rainfall Data ◽  
Cotton Yield ◽  
Rainfall Analysis ◽  
First Order ◽  
Successful Prediction ◽  
Probability Methods ◽  
Climatic Elements

<p>Curah hujan merupakan salah salu unsur iklim yang sangal berpengaruh terhadap produksi kapas Variasi hujan di lahan tadah hujan sangat linggi. Waklu tanam yang telah dilentukan sebelumnya hanya berdasarkan data curah hujan selama 1 0 Uihun Untuk mcmpcrbaiki waktu tanam tersebut, perlu dilakukan analisis hujan berdasarkan data curah hujan selama lebih dari 20 tahun untuk mendapatkan angka peluang yang lebih stabil. Analisis dilakukan berdasarkan data curah hujan lebih dari 20 tahun yang lerkumpul dari 16 slasiun hujan yang tersebar di Kabupaten Lombok Timur. lombok Tengah. Lombok Barat, Sumbawa, Bima, dan Dompu. Data dianalisis menggunakan metode peluang Markov Ordc Pertama dan perhilungan peluang sclang kering beturut-turut Waktu tanam kapas di sebagian besar I-ombok dan Sumbawa berkisar minggu pertama sampai minggu kedua Desember, minggu ketiga sampai keempal Desember di Kawo, Lombok Tengah dan Rasanae, Bima, dan minggu pertama Januari di Moyohilir, Sumbawa dan Bayan, Lombok Barat. Daerah yang beresiko linggi untuk pengembangan kapas adalah di wilayah sekilar Pringgabaya (Lombok Timur), Ulhan (Sumbawa), Donggo dan Wawo di Bima Daerah lainnya dengan kandungan air tersedia yang rendah dengan kandungan pasir lebih dari 50% seperti di 1-ape (Sumbawa) penanaman kapas hendaknya dilakukan lebih awal. Tipe iklim didominasi iklim kering dengan musim hujan yang sangat pendek sehingga tidak memungkinkan adanya pergiliran tanaman palawija-kapas Kapas hendaknya ditanam bersamaan dengan palawija mcngingal pendeknya periode hujan.</p><p>Kata kunci : Gossypium hirsutum, waktu tanam. periode kering, masa tanam</p><p> </p><p><strong>ABSTRACT </strong></p><p><strong>Prediction of rainfall probability for determination of cotton sowing times in West Nusa Tenggara</strong></p><p>Climatic elements paticularly rainfall strongly influences successful prediction of rainfed cotton yield. Rainfall vaiability varies amongst Ihe season The previous planting times were determined based on 10 years daily rainfall data. I-ongterm rainfall data arc required for rainfall analysis to get reliable probabilities. The rainfall analysis was done using Markov Chain First Order Probability and dryspell probability methods Ihe rainfall data were collected from 16 rainfall stations in West Nusa Tcnggara (Eas( Lombok, Central I-ombok, West Lombok, Sumbawa, Bima, and Dompu). Ihe planting times varied from the irst week to the second week of December for most areas of I-ombok and Sumbawa The planting limes in Kawo, Central Lombok and Rasanae, Bima were mid December: and early January in Moyohilir, Sumbawa and Bayan, West l.ombok The areas which high risk to drought are around Pringgabaya (Hast lombok), Uthan (Sumbawa), Donggo and Wawo (Bima). On sandy- areas such as I-ape (Sumbawa) cotton should be planted earlier Type of climate in most areas is dry with limited rainy season, thai relay-planting of these areas is not practiced.</p><p>Key words: Gossypium hirsutum, planting time, dryspcll, seasonal patern</p>

Global extent and distribution of wetlands: trends and issues

2018 ◽  
Vol 69 (4) ◽  
pp. 620 ◽  
Author(s):  
N. C. Davidson ◽  
E. Fluet-Chouinard ◽  
C. M. Finlayson
Keyword(s):  
High Spatial Resolution ◽  
Wetland Loss ◽  
Grand Challenge ◽  
Temporary Wetlands ◽  
Wetland Area ◽  
Time Period ◽  
Global Mapping ◽  
Real Increase ◽  
The Caribbean ◽  
Global Inventory

Herein we review estimates of global and regional wetland area from ‘bottom-up’ approaches of site or national wetland inventories and ‘top-down’ approaches from global mapping and remote sensing. The trend for increasing wetland extent reported in the literature over time is a consequence of improved mapping technologies and methods rather than a real increase in wetland area, because a continuing trend for natural wetland loss and conversion is documented over the same time period. The most recent high-resolution estimate of global wetland area is in excess of 12.1×106km2, of which 54% is permanently inundated and 46% is temporarily inundated. Globally, 92.8% of continental wetland area is inland and only 7.2% is coastal. Regionally, the largest wetland areas are in Asia (31.8%), North America (27.1%) and Latin America and the Caribbean (Neotropics; 15.8%), with smaller areas in Europe (12.5%), Africa (9.9%) and Oceania (2.9%). It is likely that estimates of global wetland area published to date persist in underestimating the true wetland area. The ‘grand challenge’ of a global inventory integrating all types of permanent and temporary wetlands at high spatial resolution has yet to be fully achieved.

scholarly journals Systematic analysis of interannual and seasonal variations of model-simulated tropospheric NO<sub>2</sub> in Asia and comparison with GOME-satellite data

2006 ◽  
Vol 6 (6) ◽  
pp. 11181-11207 ◽  
Author(s):  
I. Uno ◽  
Y. He ◽  
T. Ohara ◽  
K. Yamaji ◽  
J.-I. Kurokawa ◽  
...  
Keyword(s):  
Satellite Data ◽  
Seasonal Variations ◽  
Transport Model ◽  
Regional Scale ◽  
Horizontal Distribution ◽  
Chemical Transport Model ◽  
Vertical Column ◽  
Rate Of Increase ◽  
Increasing Trend ◽  
Good Agreement

Abstract. Systematic analyses of interannual and seasonal variations of tropospheric NO2 vertical column densities (VCDs) based on GOME satellite data and the regional scale chemical transport model (CTM), Community Multi-scale Air Quality (CMAQ), are presented over eastern Asia between 1996 and June 2003. A newly developed year-by-year emission inventory (REAS) was used in CMAQ. The horizontal distribution of annual averaged GOME NO2 VCDs generally agrees well with the CMAQ results. However, CMAQ/REAS results underestimate the GOME retrievals with factors of 2–4 over polluted industrial regions such as Central East China (CEC), a major part of Korea, Hong Kong, and central and western Japan. For the Japan region, GOME and CMAQ NO2 data show good agreement with respect to interannual variation and show no clear increasing trend. For CEC, GOME and CMAQ NO2 data show good agreement and indicate a very rapid increasing trend from 2000. Analyses of the seasonal cycle of NO2 VCDs show that GOME data have systematically larger dips than CMAQ NO2 during February–April and September–November. Sensitivity experiments with fixed emission intensity reveal that the detection of emission trends from satellite in fall or winter have a larger error caused by the variability of meteorology. Examination during summer time and annual averaged NO2 VCDs are robust with respect to variability of meteorology and are therefore more suitable for analyses of emission trends. Analysis of recent trends of annual emissions in China shows that the increasing trends of 1996–1998 and 2000–2002 for GOME and CMAQ/REAS show good agreement, but the rate of increase by GOME is approximately 10–11% yr−1 after 2000; it is slightly steeper than CMAQ/REAS (8–9% yr−1). The greatest difference was apparent between the years 1998 and 2000: CMAQ/REAS only shows a few percentage points of increase, whereas GOME gives a greater than 8% yr−1 increase. The exact reason remains unclear, but the most likely explanation is that the emission trend based on the Chinese emission related statistics underestimates the rapid growth of emissions.

scholarly journals Satellite-Based Analysis of Spatial–Temporal Distributions of NH3 and Factors of Influence in North China

2021 ◽  
Vol 9 ◽  
Author(s):  
Deng Zhi-li ◽  
Zhang Qian-qian ◽  
Zhang Xing-ying
Keyword(s):  
Relative Humidity ◽  
Emission Reduction ◽  
North China ◽  
Meteorological Conditions ◽  
Spatial And Temporal Distributions ◽  
Rate Of Increase ◽  
Increasing Trend ◽  
Factors Of Influence ◽  
High Concentrations ◽  
Global Nitrogen Cycle

NH3 is an important part of the global nitrogen cycle as the most important atmospheric alkaline gas. NH3 reacts rapidly with acidic substances and accelerates the generation of particulate matter (PM2.5), which has important effects on the atmosphere and climate change. In this study, satellite NH3 column data were used to analyze spatial and temporal distributions of NH3 in China, and because of high concentrations and rates of change, North China was selected for more detailed analysis. Qualitative analysis was conducted to understand the relations between concentrations of NH3 and those of SO2 and NO2. Last, the random forest method was used to quantify relations between concentrations of atmospheric NH3 and factors influencing those concentrations, such as meteorological factors, NH3 self-emission, and concentrations of SO2 and NO2. Satellite-retrieved NH3 column concentrations showed an increasing trend during the 11 years from 2008 to 2018, and the rate of increase in summer was faster than that in winter. In those 11 years, NH3 self-emission had the greatest influence on NH3 concentrations. Concentrations of SO2 and NO2 had some effect and were negatively correlated with NH3 concentrations. The effect of SO2 on NH3 concentration was greater than that of NO2. Atmospheric NH3 concentration was also affected by meteorological conditions (temperature, relative humidity, pressure, and wind). In summer, temperature is the most important factors of meteorological conditions and relative humidity is the most important factors in winter. Therefore, to better control atmospheric NH3 concentrations, it is particularly important to formulate practical NH3 emission reduction policies and to consider the effects of SO2 and NO2 emission reduction policies.

A robust approach for calibrating a daily rainfall-runoff model to monthly streamflow data

2020 ◽  
Vol 591 ◽  
pp. 125129 ◽  
Author(s):  
Julien Lerat ◽  
Mark Thyer ◽  
David McInerney ◽  
Dmitri Kavetski ◽  
Fitsum Woldemeskel ◽  
...  
Keyword(s):  
Daily Rainfall ◽  
Rainfall Runoff ◽  
Robust Approach ◽  
Monthly Streamflow ◽  
Streamflow Data ◽  
Rainfall Runoff Model ◽  
Runoff Model
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